To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

Wondering if a piece of writing was generated by artificial intelligence? Anthropic has a solution: Watermarks.

But the company’s recent update is not based on market demands or innovation. It stems from the European Union’s Artificial Intelligence Act. The strict rules prohibit all sorts of conduct and come with a slew of new requirements for AI deemed high-risk. Rules for "high-risk" AI went into effect this month.

Prohibitions on AI systems include "deploying subliminal, manipulative, or deceptive techniques to distort behavior and impair informed decision-making, causing significant harm." AI systems also can’t "[infer] emotions in workplaces or educational institutions, except for medical or safety reasons." And much more.

The EU AI Act’s most severe penalties are fines of up to 7% of global revenue for companies found in violation. It’s sure to make the EU a tougher place for American AI companies to do business. But the impact will be global, as seen by Anthropic rolling out watermarks in all countries, noting that the change is related to the law’s transparency requirements.

Anthropic has detailed how watermarks work, adopting a method developed and already used by Google. The process involves how the AI model chooses specific words and word fragments within the text. Anthropic has a key that involves two lists of words and the text generated must include enough of the words from one list to be statistically significant. The method has limitations, such as not working well on shorter passages and only revealing the "likelihood" of being written by AI.

"Because the watermark is part of the text, it will travel with the text when it’s copied and pasted elsewhere, and may persist through some editing," according to Anthropic. "Watermarking will be applied at the model level, which means it will be present no matter which Claude product or surface the text comes from."

If it’s working well, readers should not notice. "You won’t see it, and it doesn’t change the meaning, quality, or readability of Claude’s response," according to the company. Theoretically, watermarks could help identify AI-generated text anywhere. But the move is likely to stir up concerns about Anthropic’s power over users’ text output and what it means for intellectual property.

Expect Anthropic’s adoption of watermarks to ignite more pushback from the Trump administration, with concerns about thwarting tech innovation and harming U.S. tech giants. President Trump said last month the administration will conduct a formal review to retaliate against the EU’s "discriminatory" digital practices, stemming from another EU digital law that has led to huge fines against U.S. tech giants. The growing backlash will also focus more attention on Google’s use of text watermarks for its AI model Gemini.

With the EU’s AI Act gradually coming into full force and American AI giants working to comply, the U.S. relationship with Europe is only set to get more tense.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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When I speak with financial advisers about artificial intelligence, I often hear the same concern. Many are worried that AI will eventually replace them.

I understand the fear, as it seems that every major new artificial intelligence technology comes with predictions that this time the profession is finished. The headlines are certainly not helping, as every week there seems to be another article explaining how AI can build portfolios, answer financial questions, analyze investments or generate financial plans in seconds.

For many advisers, it may feel as if AI is attacking the very value of the practice they have spent years building.

I think that perspective misses what is actually happening.

The clients using AI are not trying to replace their advisers.

They are simply trying to become better clients.

And that distinction may be one of the most important aspects for a financial adviser to understand, and when they do, I believe it will shed a new and exciting light on the future of our noble profession.

The empowered client

For decades, many clients walked into meetings feeling overwhelmed. For your clients, financial planning can be intimidating, which is exactly why they want to work with you.

Investment terminology can feel like a foreign language. Tax code, retirement income strategies, estate planning techniques and risk management concepts are not subjects most people spend their weekends studying.

As a result, many clients sat quietly through meetings, nodded politely and left without fully understanding what had just been discussed or what action they took in their portfolios.

AI is changing this.

Clients are becoming empowered through AI and can now ask questions whenever they want. They can learn the basics of Roth conversions, Social Security strategies, charitable planning, annuities, investment management and countless other topics within minutes, but here is the key: They arrive at meetings empowered and with more information than ever before.

They no longer have to sit there and nod politely as you explain why you believe duration risk needs to be accounted for in this market, without a clue about what "duration" means.

Many advisers see this as a threat, but I see it as an opportunity because an informed client is often a more engaged client, and a more engaged client asks better questions, which leads to deeper conversations.

These deeper conversations create stronger relationships.

The adviser who embraces this rather than fights it may find that AI does not weaken the client relationship but may actually strengthen it.

The emergence of the 'confidently wrong' investor

Of course, there is an important caveat.

More information does not always create a better understanding.

AI can not only help your client feel more empowered, but it may also create a uniquely new AI-driven challenge: The confidently wrong investor.

That may become one of the most important issues for financial advisers in the next decade.

AI is trained to sound authoritative, but it is not trained to always be correct.

AI hallucinates more often than people realize. It can confidently invent IRS rules, estate planning strategies, tax interpretations and legal concepts that simply do not exist.

Sometimes it pulls from outdated information. Other times it blends accurate information with misinformation in ways that sound incredibly believable.

The important thing to understand is that AI does not feel embarrassment the way you or I would if we confidently gave somebody the wrong answer over coffee. It does not pause and think that it should double-check things. It simply delivers information with remarkable confidence, whether the answer is accurate or completely wrong.

That changes the adviser's role, as I believe the future adviser becomes something very different.

The rise of the 'Epistemic Adviser'

That is why I think advisers who fight AI are making huge mistakes. The future adviser is no longer the person hoarding information. The future adviser is the person helping clients navigate information.

That is a much more meaningful role.

I call this role the Epistemic Adviser.

Now, I realize that sounds like something a philosophy professor would say, but the idea itself is simple. An epistemic adviser is somebody who evaluates the quality of knowledge before a client acts on it.

Who said my liberal arts degree was useless?

An Epistemic Adviser is a knowledge quality inspector. Your role is no longer simply delivering information, but it is now evaluating its quality before a client acts on it.

That is a very different profession.

And here is the key: You will use AI to become the Epistemic Adviser!

You encourage your client to use AI if they want to. You will both use AI in a manner compliant with your firm. Both AIs will recommend a Roth conversion, but you are the one who knows the human side of the client, and getting her to write a $182,000 check to the IRS is something she will never do.

Both AI recommendations were for a gifting program for estate tax purposes, but the client forgot to tell the AI that she lives in Illinois, which has one of the most complicated state estate taxes I have ever seen.

Are you starting to see my point?

Both you and your client are both using AI, but you, as the Epistemic Adviser, are essential to sort it out.

The difference between knowledge and judgment

This is where advisers become more valuable, not less.

You see, you are not competing with AI. You are helping clients navigate it and think about what they are really asking for.

With the endless supply of information, they are not asking for more information. They are seeking confidence that they are making the right decisions and in the right context.

They are asking for judgment.

They are asking for someone who understands how financial decisions interact with real life.

AI may recommend delaying Social Security benefits, but it is the adviser who understands the client's health concerns.

AI may recommend a gifting strategy, but it is the adviser who understands family dynamics and state-specific considerations.

You see, the difference is not information.

The difference is judgment.

Closing thoughts

As we move forward, I believe advisers should stop viewing AI as something happening to them and start seeing it as something they can use alongside their clients.

If the client is so inclined, encourage them to bring AI-generated ideas into meetings.

• Discuss those ideas openly
• Explore them together while validating what is useful
• Explain what may be missing and help them understand not only the answer but also the reasoning behind it

Clients are not looking for replacement.

They are looking for empowerment.

And advisers who help create that empowerment may find themselves more valuable than ever in a world where information is everywhere, but wisdom remains remarkably scarce.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

These days, AI is quickly becoming part of everyday financial life.

According to a NerdWallet survey conducted in October, 43% of Americans have used artificial intelligence to help with personal financial planning. For younger generations especially, asking a chatbot about budgeting, investing or retirement is becoming as natural as searching the internet.

As CEO of Affinity Federal Credit Union, that trend doesn't surprise me. AI is available around the clock, answers questions in seconds and makes financial information easier to access than ever. For many people who have never worked with a financial professional, it's lowering barriers that have existed for years.

That's good news.

But as AI becomes more capable, I'm increasingly concerned that people are placing too much confidence in its answers without understanding its limitations. AI can be an outstanding financial assistant. It should not be mistaken for a financial adviser. Knowing the difference could save you from making an expensive mistake.

AI shines when the job is education and organization

There are plenty of financial tasks in which AI genuinely improves people's lives. If you're trying to build your first budget, understand how compound interest works, compare traditional and Roth IRAs or learn how to set up an automatic savings plan, AI can be incredibly helpful. It explains concepts in plain language, doesn't judge basic questions and is available whenever you need it.

It's equally useful for repetitive, data-driven tasks. Tracking spending, categorizing expenses, flagging unusual account activity and reminding you when bills are due are all areas at which technology excels. These jobs require consistency and speed more than personal judgment.

For many households, AI can also make financial education far more accessible. Someone who may never have scheduled an appointment with a financial professional can now learn the fundamentals of investing or retirement planning from the comfort of home. That's a positive development, particularly if it encourages people to become more engaged with their finances.

In other words, AI is very good at helping people become more informed and organized.

Where misplaced confidence can cause problems

Where I become concerned is when people begin treating AI-generated answers as personalized financial advice. Most AI platforms are designed to provide an answer, even when they don't have the full picture. That answer may sound thoughtful, detailed and authoritative, but confidence isn't the same thing as accuracy.

Researchers studying AI's role in personal finance have found that it can serve as a useful starting point, but its recommendations often remain generic because they lack the personal context that drives good financial decisions. That's the challenge.

Financial planning rarely comes down to numbers alone. The details that shape good advice often aren't found on a balance sheet. AI doesn't know that you're helping an aging parent who could soon require long-term care. It doesn't know your business partner is preparing to retire, your child has special financial needs or you're considering leaving a stressful career earlier than planned.

These are everyday realities that shape financial decisions in ways no algorithm can fully anticipate.

Similar finances don't always call for similar advice

Consider two people who are both 58. Each has $900,000 saved in a 401(k), owns a paid-off home and hopes to retire at age 65. On paper, they look almost identical. But one has a government pension and retiree health benefits. The other is self-employed, has no pension and expects significant healthcare expenses after retirement because of a spouse's chronic illness.

The numbers may be nearly identical, but the advice shouldn't be.

One household may be able to invest more aggressively because much of its retirement income is already secure. The other may need to prioritize preserving assets and building additional income reserves.

No AI tool can arrive at those conclusions unless someone first asks the right questions. Financial experts are best at interpreting these important details and suggesting the next best actions.

Money decisions are emotional

When conversing with AI, many people overlook the fact it can't recognize emotion the way a person can.

Some of the costliest financial mistakes happen during periods of fear or overconfidence. When markets become volatile, investors sometimes feel an overwhelming urge to sell everything and move to cash. During strong markets, others become convinced they've discovered a winning strategy that can't fail.

In either situation, these decisions are driven by emotions.

A trusted financial professional can hear hesitation in your voice, ask follow-up questions and help separate temporary emotions from long-term goals. AI can generate information, but it can't understand the personal circumstances behind a difficult decision or recognize when someone simply needs reassurance before making a life-changing move.

I don't believe consumers have to choose between AI and human guidance. The smartest approach is to use each when it adds the most value:

• Let AI help you organize your finances, answer basic questions, automate routine tasks and prepare for conversations about your financial future
• Rely on a trusted professional when decisions involve taxes, retirement income, estate planning, insurance, major investments or anything else that's difficult or impossible to undo

Here's a practical rule I encourage people to remember: If an AI recommendation leads you to move a significant amount of money, sign legal paperwork, claim Social Security, retire, or make a major investment decision, pause before acting.

Those are moments when a conversation with someone who understands your full financial picture is well worth the time.

Technology will continue to improve, and that's something we should welcome. AI has an important place in personal finance, particularly when it helps more people build healthier financial habits and better understand their options.

The goal is to make better decisions by combining the efficiency of technology with the perspective, context and accountability that only people can provide.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

AI is beginning to hollow out parts of the white-collar economy, and the dominant response for workers has been: Go learn a trade.

The problem is that millions of displaced professionals can't simply pivot overnight from cognitive, credential-heavy careers into physically demanding trades — without major financial and psychological repercussions.

If employers and policymakers keep pretending the answer to AI's impact on white-collar jobs is a straightforward retraining problem, they risk creating a generation of displaced professionals who feel economically abandoned by the career paths and systems they were told would protect them.

The skilled trades labor shortage isn't a manufactured narrative that appeared out of nowhere. Fields that include electrical work, HVAC and infrastructure maintenance all need workers, and younger people questioning the value of expensive four-year degrees are pursuing these pathways instead.

Not a universal solution

The problem is that the current AI workforce narrative treats the trades as a universal solution for white-collar displacement.

That framing can sound practical and reassuring. There are open trade jobs with clear demand, and career paths appear to be less susceptible to automation in the near term.

But for employers and policymakers trying to calm fears about AI, "go learn a trade" is an overly tidy answer to a far messier problem.

The scale of the disruption that lies ahead makes that answer even less convincing.

AI systems are compressing parts of the office economy.

• Marketing teams are operating with fewer people
• Entry-level analysts are competing against systems that can summarize reports, generate presentations, and handle administrative tasks in seconds
• Customer support, legal review, coding and financial services are encountering similar pressures

Recent estimates suggest AI can already perform the equivalent of more than one in 10 U.S. jobs, much of it concentrated in administrative and knowledge work.

Even a major expansion of trade training would only go so far toward softening the landing for displaced office workers.

Financial repercussions

The financial adjustment would be substantial. In many areas of the country, an entry-level HVAC technician earns just $20 to $25 an hour. This would be a difficult transition for professionals accustomed to significantly higher salaries.

Construction-related trade work is stable, valuable work, but it also represents a major reset for a midcareer professional who may have spent 15 years building a six-figure career in an entirely different field.

Professional careers shape routines, social identity and long-term expectations about stability and mobility. Many white-collar workers followed the path they believed would protect them from economic volatility, only to take on debt and build households on the assumption that specialized knowledge would remain economically valuable over time.

But many of those same workers are now confronting the possibility that all or parts of their accumulated expertise might be rapidly losing market value.

Emotional repercussions as well

White-collar unemployment also carries an unusually intense form of self-blame. Professional hiring systems place enormous emphasis on communication, confidence and perceived competence.

Extended displacement can quietly destabilize marriages, physical health and long-term planning while producing a private sense of shame that rarely appears in economic data.

The earnings damage can last for years, even if workers find employment again. This is particularly true when they re-enter the workforce in lower-paying sectors with weaker upward mobility.

Over time, that shift becomes more than a temporary decline in income, as it can reshape lifestyles, retirement expectations and social positioning.

Part of what makes the current AI transition so destabilizing is that it targets cognitive and status-based work. Traditionally, repetitive manual labor has been the most vulnerable during previous waves of automation.

AI training evolves quickly

The historical record for retraining deserves a realistic assessment before we determine what comes next. Large-scale workforce retraining efforts have struggled for decades to consistently return displaced workers to their prior earnings levels, often because they eventually land in lower-paying occupations with weaker upward mobility than the careers they lost.

The pace of AI development presents greater challenges. Technical skills in areas such as data, software and operations are evolving quickly. Reskilling curriculum can struggle to keep up with the systems that workers are being asked to learn.

A more nuanced workforce strategy would treat transition support as a broader economic issue instead of a narrow training initiative. Technical retraining is always necessary, but workers will also need clear transition pathways to navigate environments where the ground is constantly shifting beneath them.

The pace of AI development presents greater challenges. Technical skills in areas such as data, software and operations are evolving so quickly. Reskilling curriculum can struggle to keep up with the systems that workers are being asked to learn.

A more nuanced workforce strategy would treat transition support as a broader economic issue instead of a narrow training initiative. Technical retraining is always necessary, but workers will also need clear transition pathways to navigate environments where the ground is constantly shifting beneath them.

Midcareer workers navigating abrupt displacement might need counseling and temporary income support alongside technical certifications training and job placement.

Some companies are already funding skilled trades programs tied to infrastructure and manufacturing demand.

Still, those efforts were built to address labor shortages, not to accommodate large numbers of displaced white-collar workers.

There are still many unknowns. AI could ultimately reshape more jobs than it eliminates, and many professions might evolve through human-AI collaboration rather than outright replacement.

But uncertainty is not a strategy.

If large-scale workforce disruption materializes, retraining in trades alone will not be enough. A comprehensive response that includes soft skills development, job placement assistance, mental health support and some form of income assistance will be essential to preserve both economic opportunity and social stability.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

SpaceX is going big with Terafab, which it says will be the largest chip-making plant in the world when completed. But it’s hard to know if Elon Musk’s extraordinarily ambitious semiconductor plans will work.

One thing is certain: Musk is serious about building it. SpaceX is dedicating nearly $17 billion for the initial phase of the advanced semiconductor manufacturing factory, and tens of billions more in spending is likely. When finished, the company says Terafab will span 100 million square feet, making it one of the largest manufacturing facilities in the world.

Within Terafab’s walls, SpaceX will manufacture, package and test advanced logic and memory chips. The reason for entering the market is based on Musk’s sky-high forecast of the chips needed for driverless cars, humanoid robots and orbital data centers for both SpaceX and Tesla.

SpaceX says its demand for chips will eventually be so astronomical — more than the current global supply — that it can’t rely on leading chipmaker Taiwan Semiconductor Manufacturing Co. for all its needs. Or Intel, which is working overtime to start a division that makes chips for outside companies, and which has partnered with SpaceX to help build Terafab.

"Elon has a proven track record of reimagining entire industries," said Intel’s CEO Lip-Bu Tan when the partnership was announced. "This is exactly what is needed in semiconductor manufacturing today."

Will chipmaking be reimagined by the world’s most dominant space company? The answer is unclear, but here are some of the early questions we’re pondering.

1. Can SpaceX build a successful semiconductor fabrication plant?

Semiconductor manufacturing is incredibly costly and challenging. It pushes the limits of physics, chemistry and engineering. The clean rooms are up to 1,000 times cleaner than an operating room. The lithography machines needed to print chip patterns on silicon wafers cost hundreds of millions of dollars. There are specialty gases and chemicals, along with all sorts of automated machinery. The ecosystem involves thousands of suppliers around the globe.

And the economics don’t work unless the facility is running at full capacity, churning out finished wafers with a miniscule amount of defective chips. To add to the challenge, SpaceX wants to push the limits of current chip manufacturing, saying it will be the first to do so many of the processes under one roof. "The most epic chip-building effort in the world," says the company.

Musk says that eventually, a huge production volume will allow Terafab to test and develop new chip designs rapidly, calling the way current chipmakers operate "extremely conservative." He also wants to harness new physics and chip technologies, saying in a presentation, "We’re going to try a bunch of wild and crazy things."

2. How will Terafab distort the chip ecosystem?

SpaceX will become another big spender on chip equipment. The company needs advanced photolithography machinery from Dutch company ASML, pitting it against TSMC, Intel, Samsung and others. Plus, it will need to buy all sorts of other gear that goes into a leading-edge chip plant from Lam Research, Tokyo Electron, KLA Corporation and many other suppliers. Building a cutting-edge chip plant can already cost more than $30 billion and Terafab, with its scale and ambition, will cost far more.

SpaceX is also likely to poach top chip talent from other top companies. The U.S. chip sector already has a severe shortage of workers to operate chip plants. The massive project will take up lots of skilled construction labor as TSMC, Intel, Samsung and chip companies try to expand in the U.S. Over the long term, there’s the question of whether Terafab’s chip production could affect the sales of other chip leaders.

Musk’s viewpoint is that there will be an ongoing, huge shortage of chips compared with the exploding demand for AI compute. SpaceX says Terafab chips are solely for its own internal use, but one has to wonder if the company would ever consider selling its chips to outside customers. Or even making chips for customers. Plus, if SpaceX can eventually win more AI market share, that affects the chip market. Its AI competitors would need to buy fewer chips.

3. What kind of turmoil will SpaceX cause for chip stocks?

In the coming years, some investors may start monitoring SpaceX’s competitive threat to other chipmakers or even start worrying about a potential glut of chips. SpaceX wants other chipmakers to expand production as it makes plans to wean itself off outside chips. "While we are deeply appreciative of our current chip suppliers, and encourage them to expand production whenever possible, this looming gulf between supply and demand is at the core of Terafab’s necessity," according to the company’s latest update.

It wouldn’t take SpaceX completing the project or even making chips in high volumes to affect other chip stocks. Hitting early milestones or even building a promising narrative around Terafab could spark stock gyrations. Intel’s partnership with Terafab could become an uncomfortable one in years to come if SpaceX starts to be a competitive threat. Consider that SpaceX’s long-term plans for Starlink to take on terrestrial wireless carriers have already hit telecom stocks, causing U.S. wireless carriers and tower firms to trade lower.

4. What does this mean for Nvidia?

Over the short term, not much. But SpaceX takes the long view, and that’s where things get interesting. As SpaceX pursues manufacturing its own chip designs, it could mean trying to move past Nvidia, at least in the very long term. For now, SpaceX is all-in on Nvidia chips, recently committing to the company’s AI chips for its orbital data centers. "We have decided to build exclusively on Nvidia, because we think the Vera Rubin architecture is the best architecture," Musk said during SpaceX's recent earnings call.

But over time, that relationship could get challenged if SpaceX somehow is able to make its own chips and become a dominant force in AI data centers, on Earth and in space. SpaceX’s investor prospectus underscored how it wants to keep all options on the table: "While Terafab is intended to expand our internal chip manufacturing capabilities and alleviate potential future AI chip shortages at SpaceX, particularly as we pursue orbital AI at scale, we expect to continue sourcing a significant portion of our compute hardware from third-party suppliers."

What is the timeline for Terafab?

While the initial construction has started, the time it will take to produce viable chips is anyone’s guess. And there’s a difference between just making chips and producing them economically at scale. It’s likely that SpaceX faces all sorts of technical challenges in coming years.

Here are some of the key dates up to today: SpaceX announced in March 2026 that it was building Terafab in collaboration with Tesla. The partnership with Intel was announced in April 2026, which will include Intel lending its manufacturing expertise to help with design, fabrication and packaging. The latest announcement about breaking ground on Terafab in Grimes, Texas, happened on August 6 and included an aerial shot of the futuristic-looking facility.

Other development timelines, milestones and spending haven’t been determined yet (or at least are not public). It’s likely SpaceX moves aggressively on this project and the timeline for initial production is faster than other chip plants built in the U.S. However, completing the full vision of Terafab would take many years, extending well into the 2030s.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Nine in 10 midsize businesses plan to implement AI in 2026, according to J.P. Morgan's latest Business Leaders Outlook survey. But while it's incredibly easy for companies to simply "turn on" AI tools, poor AI implementation in the workplace is a growing cause of employee burnout and disengagement.

For businesses, adopting AI isn't just about technological capability. How it fits into a company's culture and systems is just as important.

AI tools as standard

Thanks to tech companies' race for AI dominance, it's never been easier for businesses to become "AI-optimized." Enterprise software now comes with AI integrated into email and basic productivity tools as standard, which means teams can use tools such as Windows Copilot or Google Gemini for practically anything.

But it's often given to employees without clear instructions or guidance. The AI tools employees most commonly use are large language models that run on user-generated prompts and back-and-forth dialogue, so most leaders assume their staff can and will figure it out for themselves.

It's imagined that through back-and-forth prompt engineering, they will eventually get the outcome they're looking for.

Research has revealed a significant gap between companies' desire to use AI and their employees' understanding of how best to do so. According to Slingshot, 77% of employees report being confused about how to use AI in their jobs, while 56% of employees in a KPMG report said they were making mistakes as a result of AI.

This hugely transformative technology is being unleashed on employees. Instead of guiding them through how to use it, it's being treated like a simple tool they can "figure out" for themselves. That is a damaging mindset for businesses and their employees, and it risks client security, employee satisfaction and burnout.

This is why leaders should develop a structured, change-management process — one that considers the risks and governance of AI within the business.

AI has the potential to transform company culture for the better, but only if the technology is rolled out in a way that fully recognizes the dynamics surrounding it. Here's how firms should be rolling out AI tools to their employees.

1. Start with vision

Companies that want to be fully AI-optimized need to start by developing a plan and a vision for their AI use. With a tool like AI that has so many potential uses, this vision offers employees a framework to address their concerns.

Rather than being fearful that they're simply training their replacement or frustrated that they're being asked to do something else on top of their regular job, a vision allows leadership to articulate how they expect AI to change the way individuals work — and, equally significant, what won't change.

2. Start small

While the ease of AI integration makes it possible for companies to grant everyone immediate access, that's not the best practice for successful implementation. Change requires buy-in and sponsors from peers and leaders, which is why any AI should be rolled out with a small pilot cohort to gain support, work out kinks and prove where it works best in the business.

Company-wide technology mandates can cause stress and resentment, but having cohort champions who can co-sign that this technology really does improve efficiency builds trust.

It also creates peer-level support systems so that, when a company-wide rollout finally does come about, employees know who can help troubleshoot problems and pass on best practices.

3. Build a culture of trust

One of the most significant ways that AI differs from most other technologies — especially more specialized digital industry tools — is that it's not perfectly honed. AI continues to evolve and make mistakes — but the only way companies can improve AI use is through a culture of trust.

Employees need to be comfortable enough to raise their hands when things aren't working, but also vulnerable enough to share when they think they've uncovered something new. Refining AI use is an experimental process, and that can be deeply uncomfortable for those used to more black-and-white processes and cultures.

Firms that want employees to use AI have to set new standards within their culture, elevating and celebrating incidents in which employees are willing to learn and share through collaborative problem-solving.

The bottom line

As AI continues to proliferate across the corporate landscape, having a clear change-management plan for its introduction isn't a nice-to-have: It's a critical need. Successful AI use won't happen on its own — especially at firms that haven't invested in the culture of trust AI needs to succeed.

Employees are crying out for guidance. In the 2025 AI at Work survey, 61% of employees said they want more transparent communication from leadership about AI use. It's up to leaders now to deliver.

Companies need to adopt AI to remain competitive, but without thoughtful change management, they're destined to fall behind.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

More than half of U.S. adults have not completed any of their core estate planning documents.

That comes from a recent report by Trust & Will, and this gap in estate planning preparedness is often caused by the misconception that estate planning is reserved exclusively for ultra-high-net-worth individuals, or people with $30 million in liquid or investable assets.

In reality, an "estate" simply refers to an individual's total assets and belongings.

As a CPA, financial planner and wealth adviser, I like to sum up estate planning with the following question: If something happens to you, what happens next?

Elements of an estate plan

An effective estate plan relies on four core documents:

• Last will and testament
• Durable power of attorney
• Healthcare proxy
• Living will

Establishing these safeguards can help carry out your estate planning objectives and may reduce the likelihood that your family will need to navigate a lengthy and complicated probate process.

It is a common misconception that next of kin automatically have the right to step in during a medical or financial crisis. Simply being a son or daughter does not grant them legal authority.

By putting these specific documents in place, you give your loved ones the tools they need to manage two of the most important aspects of your life: Your health and your finances.

Claiming 'control'

The key word in estate planning is control. But what does it actually look like to lose it?

Without a plan, the everyday financial security you've spent a lifetime building can instantly slip out of reach. Reclaiming that control requires appointing a trusted executor and clearly mapping out your beneficiaries.

Crucially, you must communicate with your chosen executor before finalizing your paperwork to ensure they are genuinely willing and able to shoulder this heavy responsibility.

True financial control also means protecting your heirs from their own financial choices. That is why I often help clients "ladder" asset distributions by age or embed specific provisions tailored to unique family dynamics, which helps in seeking to ensure your hard-earned wealth hits the right hands at the right time.

A lack of planning can also impact your control over your health and your family's ability to advocate for you. If a sudden medical emergency leaves you incapacitated, you lose your voice entirely.

Without an advance healthcare directive or a designated medical power of attorney, your loved ones are left guessing in a hospital waiting room, paralyzed by the difficult choices during an already traumatic crisis.

By formalizing your medical wishes in advance, you maintain control over your care. You get to decide which life-prolonging measures you want, or don't want, dictate your preferences for comfort care and legally empower a single, trusted person to speak on your behalf.

Ultimately, healthcare estate planning helps ensure your family members don't have to make difficult decisions in a state of grief and can focus on healing.

Estate planning in the age of AI

We live our lives online, and in the age of artificial intelligence (AI), it is incredibly tempting to use software to automate your estate plan.

While technology can be a valuable resource, it shouldn't replace thoughtful conversations with a qualified financial professional.

Relying on an algorithm introduces a potential liability gap. Estate laws are highly nuanced, and if an AI tool makes a mistake or misses a state-specific loophole, the legal and financial fallout can land on you and your family.

For example, in my home state, we have Tennessee Community Property Trusts, a specialized, revocable joint trust that allows married couples to convert their individual or jointly held assets into community property.

While Tennessee is naturally a "separate property" state, this trust allows couples to opt in to community property laws that may help maximize tax benefits.

These nuances highlight the importance of working with a financial adviser and attorney with boots on the ground in your state who can keep a pulse on new laws or rules and present options you may be interested in exercising.

More importantly, estate planning is not a sterile transaction. It is a road map for your family's most difficult moments.

An algorithm cannot sit with your grieving spouse or guide your children with empathy, but a financial professional who has taken the time to understand your family and its unique dynamics may be a valuable source of guidance and support during a difficult time.

Your action plan

So, where do you go from here? Even if your financial situation doesn't require complex, high-net-worth trusts, there are practical steps you can take today to take charge of your future.

I recommend starting with a personal balance sheet. Bringing your cash flow and assets into clear focus removes the intimidation factor and gives you a concrete starting point.

With that financial snapshot in hand, many individuals begin by establishing the four core documents as a foundation for their estate plan.

From there, remember that an estate plan is a living and breathing document, not a one-time transaction. It may be beneficial to review your plan annually, or sooner if you experience a major life milestone, such as the birth of a child or grandchild.

Your finances will naturally evolve over time, and keeping your plan aligned with your growing assets can help ensure your wishes remain accurate.

Ultimately, this consistent upkeep is what helps create a lasting framework for future generations.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

It can feel like every day brings a fresh batch of headlines about the financial promise of artificial intelligence. But alongside that excitement is a growing concern: What if we're in an AI bubble?

The question isn't just for investors who own AI-specific stocks. The Magnificent Seven — virtually all of whom are making massive investments in AI — now account for roughly one-third of the S&P 500's value.

With Americans holding a record 33% of their wealth in stocks, and a relatively small group of tech companies driving an outsized share of returns, you may be invested in AI without even realizing it.

Fortunately, caution doesn't necessarily require abandoning the stock market or avoiding AI altogether. The goal is to build a portfolio that can benefit from the technology's growth potential without tying your financial future too closely to a single trend.

Why some investors are concerned about an AI bubble

Many investors see echoes of the dot-com era in today's AI boom. In the late 1990s, internet stocks soared as investors rushed to profit from a world-changing technology. But when the market bubble burst, many companies failed and investors suffered steep losses.

This story contains an important lesson for today: Investors can be right about a technology and still lose money.

Remember, you can't "bet" on artificial intelligence itself. Some companies involved in AI may have the potential to become long-term winners, while others may never generate the profits some investors might currently expect.

That doesn't mean there is definitely an AI bubble. But it does mean investors should be mindful of how much of their portfolio depends on a relatively small number of companies and distant expectations.

Five ways to manage AI risk in your portfolio

Whether AI is in a bubble is ultimately beside the point. Investors don't need to predict when enthusiasm has gone too far. The aim is to participate in the technology's potential for upside without becoming overly dependent on it.

Here are five considerations to help guide your investment decisions:

1. Understand your real AI exposure

Many investors own AI-related companies through S&P 500 funds, Nasdaq funds, growth funds, technology ETFs and employer stock. You might think you have a diversified portfolio, when in reality you could be invested in the same handful of large technology companies across separate funds.

2. Consider prioritizing companies with strong current profits

Valuations are often just expectations of future growth, not evidence of current earnings. Investors concerned about volatility may also favor lower-beta stocks, which tend to be less sensitive to broad market swings and speculative enthusiasm.

3. Consider AI infrastructure instead of AI speculation

Investors might consider companies that support the broader AI ecosystem — including semiconductor manufacturers, data-center operators, power providers and enterprise software firms. These businesses stand to benefit from AI adoption regardless of the form it ultimately takes.

4. Consider diversification beyond AI

Even if you're optimistic about AI's long-term potential, it shouldn't necessarily become the defining driver of your portfolio. Exposure to a variety of other sectors and asset classes can help reduce dependence on a single theme.

5. Consider rebalancing rather than trying to time the market

Review asset allocations regularly, consider trimming positions that have grown disproportionately large and possibly reinvesting in underrepresented areas. Rebalancing can help manage risk no matter where the market turns, but keep in mind that rebalancing, asset allocation, and investment diversification do not guarantee a profit or protection against loss in a declining market.

You don't need to know whether AI is a bubble

No one knows whether today's AI boom will end in a bubble or continued growth. But investors don't need to predict the outcome to be prepared.

By understanding their exposure and avoiding excessive concentration, they can participate in AI's potential upside without tying their financial future to the possibility of success of a handful of companies.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Three decades ago, buying a stock required a phone call to a broker, a sizeable fee and the confidence to act on limited information.

Today, a client can analyze their portfolio, stress-test retirement plans and execute trades before finishing their morning coffee. I've seen this transformation unfold remarkably quickly over the course of my career in this industry, and it is still accelerating.

But as technology has made financial planning faster, cheaper and more transparent, it has also introduced a new category of risk — the illusion of certainty. More data and authoritative-looking outputs do not always produce better decisions. And in retirement planning, the gap between what technology can model and what it cannot understand is consequential.

From gatekeeping to empowerment

The shift in financial access over the past generation has been profound. High fees and limited platforms once kept most investors dependent on intermediaries for even basic transactions. The emergence of online brokerage accounts, zero-commission trading and real-time data fundamentally changed that dynamic — and the nature of the adviser-client relationship itself.

Clients come to meetings better informed, ask sharper questions and hold advisers to a higher standard of transparency. That accountability is healthy. It pushes advisers to be more rigorous and to communicate with greater clarity.

Technology has freed advisers from operational tasks that once consumed a disproportionate share of the day. Investment selection, trade execution and portfolio rebalancing were painstaking manual processes at one time.

Today, they are largely automated. That shift allows advisers to direct their attention toward the work that matters most: Understanding a client's values, goals and concerns in ways that no algorithm can replicate.

The promise — and limits — of artificial intelligence

Artificial intelligence (AI) has become the most discussed tool in financial planning — and with good reason. AI-powered platforms can process vast datasets, generate retirement projections and identify tax-planning opportunities in a fraction of the time it would take a human adviser working manually.

But while I'd recommend using AI tools to prepare for advisory meetings, they can't replace them. When clients arrive having already worked through an initial plan, the conversation moves past the basics to focus on the decisions that are genuinely complex.

• How do we plan for a child with special needs?
• What does retirement look like for someone who intends to keep working part-time?
• How do we balance competing obligations to aging parents and a college-bound teenager?

These are not questions AI can answer without truly knowing the client, and they are often the most significant.

There is also a subtler risk that plays out more than once in any advisory practice. Clients often assume that because a plan was generated by a sophisticated platform, it is fully personalized to their situation.

In reality, AI outputs are only as good as the inputs they receive. A projection built on incomplete or inaccurate information can create overconfidence — a false sense of retirement readiness that goes unexamined because the output looks authoritative. The plan may be technically sound but emotionally incomplete.

It's important to view AI not as a threat but as infrastructure — a foundation that makes advisory work faster and more precise, while leaving the interpretive and relational dimensions of planning firmly in human hands. The financial advisers who thrive in this environment are not those who resist technology, but those who integrate it thoughtfully.

Beyond the headline technology

AI has been behind some of the most consequential improvements in financial planning. Tax planning is a good example. AI-assisted platforms can now model complex strategies around Roth conversion timing, charitable giving and capital gains harvesting — work that previously required hours of manual effort.

Advisers still review and refine these outputs, but the platform does most of the analytical heavy lifting, enabling more sophisticated planning to reach a broader range of clients.

Automation has simplified everyday financial management for clients as well. AI-powered note-taking tools now capture meeting conversations accurately and feed them into client management systems.

Context from one meeting is preserved and accessible in the next, which is incredibly valuable for maintaining continuity in long-term advisory relationships.

Where human judgment remains irreplaceable

Perhaps the clearest illustration of technology's limits can be seen at the transition from accumulation to distribution — the shift from building wealth to drawing it down. This phase involves products and strategies, including certain annuities, long-term care solutions and income-layering approaches that are typically available only through licensed advisers.

A client relying entirely on self-directed digital tools may not know these options exist, let alone understand how to evaluate them. Bridging that gap is what advisers are for.

Then there is behavioral finance. Markets decline. Plans require revision. Life circumstances change in ways no projection anticipated. In these moments, an adviser's role is not primarily analytical — it is steadying.

The conversations that matter during a market downturn, job loss or unexpected health crisis have nothing to do with spreadsheets.

Helping someone hold a long-term perspective when emotion is pulling in another direction is a distinctly human skill, and one with real financial consequences.

Avoiding costly mistakes in times of volatility can impact retirement outcomes as much as years of disciplined saving.

As automation handles more of the technical work, advisers get to focus on the aspects of planning that are most personal, complex and consequential. That is not a smaller role — it is a more meaningful one.

A more useful question

The right question about technology in retirement planning is not whether to use it. The better question is how to use it well and where to recognize its limits.

The clients who navigate this environment most effectively treat digital tools as a starting point, not a final answer. They use AI platforms to build initial frameworks, then bring them to an adviser who can pressure-test the assumptions, account for the intangibles and translate a spreadsheet into a plan that reflects how they want to live. Technology makes that conversation more efficient. It does not eliminate the need for it.

In a world where financial data is more accessible than ever, the scarcest resource in retirement planning is no longer information. It is the discernment to use it wisely —and that is still a very human strength.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Medical billing mistakes are an expensive epidemic in American healthcare.

Studies consistently show that a staggering majority of hospital invoices contain errors, ranging from double billing to miscoded procedures.

For decades, consumer advocates have given the same advice: Request an itemized statement and review the codes. But for the average patient, staring at a sheet of five-digit current procedural terminology (CPT) codes is like trying to read hieroglyphics.

Fortunately, the balance of power is shifting. Generative artificial intelligence (AI) tools such as OpenAI's ChatGPT and Google's Gemini have emerged as powerful personal finance assistants.

By feeding cryptic billing logs into these AI platforms, consumers can instantly break down complex medical jargon, verify insurance logic and pinpoint specific overcharges that human eyes routinely overlook.

The AI audit in action: A case study

To understand exactly how this works, let me share a real-world analysis related to Mohs surgery I underwent earlier this year. Upon receiving my itemized statement from my medical provider, I compared it with my insurer's explanation of benefits (EOB).

The sticker price was a dizzying $3,802, loaded with confusing five-digit codes and multiple offsetting entries, and my insurance covered just $1,390, leaving me responsible for $2,412 out-of-pocket.

That's when I turned to Gemini.

I snipped the detailed information from my bill and saved it as a PDF, keeping my personal information private. I uploaded the document to Gemini with the following prompt: Analyze this bill and tell me what the codes mean and assess whether the insurance coverage is correct.

Gemini systematically untangled each line item to explain each in easy-to-understand terms.

The AI discovery: The consultation trap

Beyond mapping codes to plain English, AI's real value lies in its ability to cross-examine billing logic against standard insurance rules. AI successfully verified that the provider was treating me as an "in-network" patient due to the presence of "Code 3000-Contractual Write-Offs" across seven distinct entries.

The AI mathematically validated that the write-offs properly reduced the gross retail price to an allowed contract amount.

But critically, AI flagged a glaring systemic discrepancy that I should inquire about, in this case an office consultation fee. AI flagged that there was a very high probability that this consultation line was being contested or denied entirely by the insurance provider.

Insurance companies generally bundle the initial evaluation into the surgical procedure if they happen on the same day, unless the doctor evaluated a separate, unrelated medical issue during that same visit.

In my situation, there was no such "consultation." I had been referred to the Mohs surgeon by my regular dermatologist after a biopsy.

Because the itemized bill split the write-offs across multiple entries for "technical" and "professional" components, it effectively masked whether the core consultation line was rejected and pushed directly onto my out-of-pocket responsibility.

After calling the provider and disputing the charge, they removed the office consultation fee of $269.

Your step-by-step guide to auditing bills with AI

If you want to put ChatGPT or Gemini to work on your medical bills, follow this strategic blueprint to ensure accuracy and protect your financial interests:

Secure an itemized bill. Don't rely on the summary invoice that simply demands a "balance due." Call the provider's billing office or log into your patient portal and request an itemized statement showing CPT codes, revenue codes and logged contractual write-offs.

Redact sensitive information. Before uploading any document or typing text into an AI model, scratch out your name, Social Security number, address and policy ID number to protect your medical privacy.

Deploy a structured audit prompt. Feed the text or a clear image of the bill into the AI. Use a direct prompt such as: "Act as an expert medical billing advocate. Decode these CPT codes, explain what procedures were done, calculate the total write-offs, and check for standard insurance logic errors."

Cross-reference with your EOB. Never pay a hospital bill until you match it against the explanation of benefits (EOB) mailed by your health insurer. If the AI identified a contested line — such as the 99243E consultation fee — verify if your insurer passed 100% of that charge onto you.

Arm yourself for the dispute. If the AI spots a bundling error or an overcharge exceeding the allowed contract threshold, call the medical provider's billing office.

If appropriate, you can ask them to apply a specific modifier to prove the consultation was distinct from the surgery, or dispute the charge entirely if no separate consultation took place. Know that mistakes can occur in coding that cause insurers to not cover otherwise covered procedures.

The bottom line

Artificial intelligence won't write a check for you, but it acts as a free, highly trained financial advocate.

Spending 10 minutes running your medical invoices through an AI model can prevent you from paying hundreds of dollars in automated administrative errors.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Usually, there are crosscurrents in financial markets, but today's seem particularly demanding.

The war in Iran seems always there, affecting short-term policies while being a longer-term problem. We don't know where it will go, just that the on-again, off-again intensity of the war affects the stock and bond markets.

Adding to this scenario is AI. Artificial intelligence is very promising, but it's hard to determine who the big winners are. The staggering sums of money that companies are investing in AI is worrying many investors, while the earnings that AI-related companies are reporting are impressive.

But will that growth continue and at what pace? This clouds the longer-term outlook.

Some investors are throwing their hands in the air and selling all or some of their equity holdings.

Here's an option: Fixed income

Meanwhile, fixed income is attractive, with rates having risen. For example, the 30-year Treasury bond is back up to about 5%, a number that hasn't been seen except for brief periods since July 2007.

The U.S. Treasury securities market has grown substantially, and individual investors have participated in its growth. Treasuries carry the U.S. government guarantee of timely payment of principal and interest. The interest that U.S. Treasuries pay is exempt from state and local taxes. This makes them the highest-quality investment of their type.

So, what is the best way to buy Treasury securities?

The go-to way to trade Treasuries used to be to visit TreasuryDirect.gov, but not anymore. The much larger Treasury market has flooded TreasuryDirect and made it impossible for the site to keep up with demand.

There are many reasons for this growth, including the increased share of insurance companies, money market instruments and broker-dealers buying Treasuries; the Federal Reserve shrinking its balance sheet; and pension funds and other institutions increasing their holdings.

The result is that the site recently reported delays in its response to fill mail requests. Among other delays, it could take nine months to complete converting paper savings bonds into electronic bonds. To cash paper savings bonds could take at least three months.

And requests to find lost, stolen or missing savings bonds would take a minimum of 11 months to process.

More bond trading

Bond trading volume is probably going to increase. Kevin McPartland of Crisil Coalition Greenwich reported in April that corporate bond market trading hit an average of $65 billion traded per day in March.

This was a record, surpassing the volume of the previous month, which was also a record.

Also, on the last day of March, $108 billion was traded, a single-day record for bond trading.

McPartland also pointed out that this higher bond volume was partly being facilitated by the advanced electronics used by institutional traders.

Another factor is that developed execution management systems are being employed, along with more standardized post-trade processes.

He pointed out that even though the systems and tools are more advanced, good people handling the processes are still needed. "Traders want a human element even when trading electronically," he wrote.

How to buy and sell fixed income, including Treasuries

Brokerage firms have always offered fixed-income securities, including Treasuries, but they have improved the ways for investors to buy and sell, even for small amounts. For example, the electronic trading platform Public has secondary market liquidity, an easy-to-navigate interface and other advantages.

Although bonds usually trade in $1,000 increments, Public trades corporate bonds and Treasuries in as few as $100 increments.

Investors can also build ladders at Public, spreading maturity dates to match investor needs. This can be done with Treasuries or bonds. Investors can call Public anytime, day or night, for support.

Another broker, Charles Schwab, advises that certificates of deposit (CDs) and Treasury bonds are two of the safest fixed-income investments you can make. And both can add diversity to your portfolio, generate income and protect principal. (Schwab also points out that investors can lose money in these securities.)

Schwab, like other brokerages, has fixed-income specialists available for calls from investors, as well as in-house traders who can be contacted either by phone or online. Schwab additionally builds taxable and tax-free Treasury and bond ladders for investors.

Fidelity Investments created a fixed-income site that offers a wide range of bonds, Treasuries and other offerings — 75,000 to 100,000 new issues and secondary securities are offered.

Fidelity charges only $1 markup or markdown for bonds traded in the secondary market; it charges no fee for online U.S. Treasuries.

For qualified clients, it offers help from fixed-income specialists and provides a high-net-worth desk to help investors with bonds and CDs.

Interactive Brokers (IBKR) is another broker committed to upgrading bond trading to a new standard and doing it on a worldwide basis.

On its platform, investors can invest globally in many financial securities, including equities, options, currencies, futures, bonds and funds. Accounts can be funded in many currencies, and trades can be denominated in different currencies. Market data can be accessed six days a week, 24 hours a day.

Thomas Frank of IBKR said, "We aim to provide our clients with the most flexible and comprehensive trading environment possible."

To that end, IBKR offers over 1 million corporate, municipal, non-U.S. sovereign bonds and Treasuries. These are offered without markups or built-in spreads.

ETFs that are unique

The professionals at investment management firm F/m Investments believe that investors have sent a clear message — they want safety, and they want to be shielded against inflation.

According to F/m, that's why investors poured $25 billion into ultra-short-duration U.S. Treasury ETFs. The funds started coming into the ETFs — BIL, SHV, SGOV and TBIL — at the outset of the Iran conflict and took only six weeks to be deposited.

The reason for the investment surge, according to F/m, is that these ETFs pay an attractive rate.

Also, if the conflict raises inflation further, these ETFs can reset soon to receive higher yields. And principal is protected because these securities will fall less than longer-term bonds as a reaction from the market adjustment to the higher rate.

F/m offers investors its single-maturity Treasury ETFs, called the U.S. Benchmark Series. The series makes it possible to buy Treasury ETFs during stock market hours and lock in the current on-the-run yield. On-the-run refers to the securities most recently auctioned. The securities are held only until the next auction, and they are sold, with the proceeds being used to buy a new series being auctioned.

The U.S. Benchmark Series is available in the full maturity range of Treasury bills, bonds and notes. This includes all securities from the 3-month Treasury bill ETF (TBIL) to the 30-year Treasury bond ETF (UTHY).

Treasury yields are attractive, even at the short maturity end: The TBIL yield is 3.54%; UTHY is 4.85%. This yield will change throughout the trading day; the market price will price in changes. The market price of publicly traded Treasuries and other income securities, in an ETF structure or individual securities, will fluctuate, and money can be made or lost.

The U.S. Benchmark Series offers maturity date diversification. As interest rates fluctuate between the series offerings, investors can switch into a higher-yielding Treasury or stay where they are.

The ETF series attempts to pay interest monthly, another advantage over holding individual Treasuries. The expense ratio is reasonable at 0.15% per annum.

Navigating today's volatile markets requires staying informed and being flexible, but whether you choose to buy individual Treasuries through a brokerage or opt for the simplicity of ETFs, there are reliable tools to help you protect your capital and generate steady income.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

If you are being billed by the hour for professional services, now is the time to renegotiate, as AI has put the billable hour on life support.

In January 2024, during his recuperation from surgery and radiation treatment of thymoma — an extremely rare cancer — Los Angeles-based attorney Aaron Shechet, "wanted to do something for my wife and law partner, Leigh, who proved what being there 'for better or for worse' means. She said, 'Make an app that helps me bake better sourdough.'

"So I built an app to take pictures of her sourdough bread — AI analyzes the picture and tells how to improve it. It came out so good that I released it on Android and Apple."

Then an idea came to Shechet. "What if I could develop a platform that helps service providers, accountants, lawyers and other professionals use AI programs that would save them hours and result in significant cost savings to their clients?"

Veilgrid was the result. "It is a platform that creates custom AI-powered tools tailored to specific business activities," he notes, "such as drafting contracts, leases, various sorts of documents and automating related office functions, saving upwards of 75% of the time required to do the same work manually."

AI impacts professionals and their clients/customers

Shechet has been a mediator and fee arbitrator in Los Angeles for years, and he has impressed me with his concern for clients trapped in billable-hour spirals. He sees a tsunami coming to those professions that view efficiency as their mortal enemy.

"Billable hours reward lawyers, accountants, management consultants — to list just a few — for spending more time on a task," he says. "Faster work — efficiency — directly reduces total revenue, as you can't bill a whole lot of hours.

"With AI, the incentive is to be more efficient, as you will invoice on the completion of work, not the hours to do the work."

He adds, "Clients do not care how the final product was produced — they just want results, the more economical the better. And they know that AI saves an enormous amount of time in producing reproducible items, such as contracts, leases, tax returns and so much more."

A new standard of care

Shechet strongly believes that the new standard of care for law and other professions, figuratively speaking, will be a $5 charge with "AI quality," instead of hundreds of dollars an hour with potentially less quality.

"What clients pay must come down," he says. (For the record, AI is wrong sometimes, so someone still needs to check the work to make sure it's accurate.)

He lists tasks where AI is most effective in law that would take hours to do manually and cost clients hundreds to thousands of dollars:

• Anything written, including contract drafting, pleadings, motions and discovery
• Summaries of depositions for senior partners that can be generated in minutes
• Legal research that requires dramatically reduced time
• Tasks that once took teams of junior associates weeks can now be completed by a single attorney in a few hours or even seconds

AI also works 24 hours a day. It doesn't have student loans or employment insurance, it doesn't complain, and it doesn't face employee lawsuits.

New billing methods

Shechet and many other observers expect to see subscription models where a lawyer, accountant or other professional is on call to handle all the matters a client needs for a flat monthly fee.

"We should also see more per-job and contingency fees," he notes, adding, "AI is no longer in the experimental stages for many professions. It is being widely adopted. Clients need to ask their lawyers, accountants and other professionals who bill by the hour, 'Are you using AI to save me money? And if not, why not? Why does this professional service cost so much?'"

What's the impact on lawyers?

I asked Shechet what impact AI will have on the human side of the legal profession.

"There will be little justification," he says, "for massive law firms — that have been compared to pyramid schemes — to reward senior partners while demanding impossible 2,000 yearly billable hours from junior lawyers. That (practice) has invited decades of bill-padding and outright fabricated work and destroyed marriages and families.

"The need for lawyers will shrink, and hopefully, the ability to go home at 5 p.m. and have dinner with the family and have a life will return to the legal profession."

For anyone considering law as a career

Shechet cautions that law can no longer be recommended as a safe, automatic path to a high-income career.

"But if law is pulling you, go for it. Follow your instincts, but do not expect the profession to look the way it did 20 years ago. Veilgrid came from following what presented itself: I built it for our practice, then other lawyers, then other professions, and finally, it became a platform.

And he cautions, "Anyone considering law should think very carefully about debt. Do not borrow an enormous amount of money because this seems like a safe profession. The supposedly safe, predictable part of legal work is exactly the part AI is commoditizing most quickly."

Dennis Beaver practices law in Bakersfield, Calif., and welcomes comments and questions from readers, which may be faxed to (661) 323-7993, or e-mailed to Lagombeaver1@gmail.com. And be sure to visit dennisbeaver.com.

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• We Gave AI Chatbots 5 Financial Challenges. Here's How They Did

This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

A pricing war is afoot among cutting-edge artificial intelligence vendors. Meta will jolt the competition with cheaper advanced AI tools for businesses from its new AI model, Muse. SpaceX’s latest Grok AI is built for efficiency and low costs, priced 60% cheaper than Anthropic. Microsoft is shifting from Anthropic and OpenAI to its own, cheaper internal AI tools for apps such as Excel and Outlook.

Meanwhile, cheaper Chinese AI models such as DeepSeek and Kimi are quickly gaining ground, though congressional investigations may lead to attempts to put curbs on the foreign tech. The latest version of Kimi, developed by Chinese company Moonshot AI, has sparked equal measures of excitement from U.S. customers and concern from leading American AI companies and federal officials. U.S. policy concerns include China’s massive government subsidies, intellectual property theft, cybersecurity risks and the general threat of Chinese competition.

The competition could put pressure on profit margins for AI leaders, which still must invest massive sums of money to develop and deploy leading tech. The latest Grok 4.5 model is a threat to Anthropic and OpenAI since it is a "'good enough,' fast, and super-cheap model," writes Neil Shah, analyst at Counterpoint Research, in a recent post. “Now enterprises have an attractive option, allowing them to optimize their AI spend before it spirals out of control.”

But there’s a catch for companies excited to see lower prices: Customers aren’t likely to save money because their AI use is rising so fast — AI is billed based on how much is consumed, which is far outpacing per-unit cost declines.

That remains true even as the long-term trends look promising for customers. Market research firm Gartner says a combination of efficiency improvements in chips, data centers, software and more will drive down prices. "By 2030, performing inference on a large language model with one trillion parameters will cost GenAI providers over 90% less than it did in 2025," according to their analysis from March.

Not all the savings will be passed on to customers, says Gartner, and cutting-edge agentic AI, which automates all sorts of computing tasks, consumes far more AI compute. "Agentic models, for example, require between 5-30 times more tokens per task than a standard generative AI chatbot," says Gartner. (Tokens are the units of data processed by AI. Companies are commonly billed by how many tokens they use.)

So what are companies going to do to reel in AI budgets? “Enterprises will learn and become prudent not to stick to one vendor or model,” according to Shah. That means that most complex tasks can be accomplished with the most expensive, best AI. Simpler tasks can be done with cheaper AI tools.

Gartner recommends that companies maintain a list of tasks that require high-end AI tools, train employees on how to reduce AI costs, post limits on individual token consumption and closely track AI usage.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Keith Ward, 61, is proud of his son, who graduated from college in December of 2025 with a degree in information systems. His son was focused during his studies and worked hard to build skills he thought would lead to gainful employment.

Instead, Ward's son is living at home and struggling to find work.

"He's applied to more than 250 jobs, and I think has gotten seven interview requests," Ward lamented. "Five years ago, employers would've been having fist fights to hire him."

Ward's son's experience isn't unique. The rise of AI has made an already tight job market for new applicants even tighter.

As of March 2026, the unemployment rate among recent college graduates ages 22 to 27 was 5.6%, compared with a 3.1% unemployment rate across all college grads, according to the Federal Reserve Bank of New York.

Underemployment is an equally big issue. As of January 2026, 41.5% of recent graduates were underemployed.

The Federal Reserve also found that as of May 2026, 15% of adults ages 18 to 29 who weren't working said they couldn't find a job, while 10% were working part-time because they were unable to find full-time work.

Ward's son is trying to stay positive. For now, he's working part-time in a bookstore.

"It's been frustrating for him because now he's living with us," Ward says. "He wants to be independent. He wants to be working in this field that he trained for. When he started four years ago, there was no thought that AI was going to be taking jobs."

It's not just Ward's son who's been struggling.

"My wife and I have been planning for retirement. Now we have three of our grown children living with us," Ward says.

Ward's initial plan was to retire within five years.

"But I don't think it's going to happen," he says now. "We're going to continue working until circumstances force us to do something else because we want to have a place for our kids to be."

A troubling trend

Ward's experience isn't unique. A late 2025 AARP survey found that 75% of parents are providing financial support to a child 18 or older. That's apt to impact a lot of people's retirement plans.

Julianne Coleman is 62 and plans to retire abroad with her husband. Now, those plans are on hold indefinitely as her two 20-something children grapple with the reality of today's workforce.

Her 22-year-old, who's a recent college grad, is especially struggling.

"I just don't know how someone like him who's relatively new to the workforce and relatively green is going to find something fulfilling," Coleman says. "There's all this economic uncertainty created by the AI bubble."

Coleman's daughter, who's 26, is in the midst of a career pivot after landing a job out of college that was too AI-heavy.

"She doesn't want anything to do with AI, even though she's well-versed in it," Coleman says. "She wants to move another way because of how damaging she sees it being."

In the near term, Coleman is spending her own resources to feed her grown kids and provide a roof over their heads. Her dream of retiring abroad hinges on being able to sell her home, which she can't do with her children living in it.

"If my kids were fully independent, we would downsize," Coleman says. But since her kids only have roughly $10,000 in savings each and limited job prospects, Coleman feels stuck.

"The next 15 years are critical in terms of mobility," Coleman says. She's afraid she'll lose out on an opportunity she saved for because her kids can't leave the nest.

Mostly, however, she feels for her kids.

"I'm sad for them," Coleman says. "I feel like we had it so much better."

Data from the Federal Reserve Bank of New York points to the fact that remote work is sidelining young job applicants more so than AI right now. On the other hand, Challenger, Gray & Christmas found that U.S. employers implemented 45,849 job cuts in June, largely fueled by AI. While those cuts weren't necessarily specific to younger workers, they speak to a worrying trend.

Adam Spiegelman, founder and wealth adviser at Spiegelman Wealth, says he's seeing firsthand how much young adults are struggling.

"In my 25 years as a wealth adviser, I’ve never seen anything like this year," he says. "I’ve received about a dozen unsolicited emails from college juniors, seniors and recent grads … asking to shadow me or intern at my firm. That’s never happened before."

The trend is much broader, though.

"Many of my own clients are telling me their kids and grandkids are struggling to find work," Spiegelman says. "Whether it’s inflation, the broader economy, AI or some combination, this generation is having a genuinely hard time landing that first real job, and I’m seeing it push some parents to seriously reconsider their retirement timelines."

Should you delay retirement because your kids are struggling to find work?

AI might not be the only reason your 20-something children can't find work. But should you be altering your retirement plans because of it?

Spiegelman says that while it's natural to want to help your grown children, he thinks it's important to separate support from enabling.

"I have a client right now who’s buying a home for his adult child to live in rent-free — a full-time, able-bodied adult with only a part-time job. That’s a very different situation from a family giving a new grad six months to a year of breathing room while they find their footing," he says.

As Spiegelman explains, both are examples of support, but only one has an exit plan.

"Parents need to have that conversation with each other first, before their child even graduates, and agree on what their expectations are and where the line is," he says.

Steve Sexton, retirement planning expert at Sexton Advisory Group, agrees.

"It's natural for parents to want to help their children, especially when they’ve done everything right," he says. "But the biggest thing I would tell parents is support your adult children in a way that does not quietly derail your own retirement."

That's easier said than done when your child can't find a job and might be sitting on a pile of student loans. But like Spiegelman, Sexton feels parents should put a dollar amount and timeline around the help they'll provide.

Most important, Sexton says, parents should avoid tapping retirement accounts, pausing retirement contributions, or taking on new debt to support an adult child.

"Your child has time to recover financially. You may not. A 23-year-old can rebuild from a tough job market, but a 62-year-old who drains savings … may have a much harder time catching up," he says.

You're allowed to fulfill your own dreams

Ultimately, there are many such parents as Ward and Coleman who are in a position to help their kids without necessarily compromising their finances as much as their dreams. But that's also a problem, Spiegelman insists.

"People spend 20, 30, 40 years working and saving so they can retire in their sixties, and that window to actually enjoy retirement — travel, health, time — isn’t unlimited," he says. "Continually pushing that back to subsidize an adult child who could be working is usually not serving anyone well, including the child."

If parents feel they haven’t set their kids up with the right financial habits, Spiegelman says it’s not too late to have that conversation now.

"Start charging rent after a reasonable grace period, and scale support down deliberately rather than indefinitely," he says.

Spiegelman also recommends bringing in a financial adviser or CPA as the “bad guy.”

"It’s a lot easier for a parent to say, 'Our adviser says we can’t keep this up if we want to retire on schedule,' than to have that conversation alone," he says.

Some young adults are as fiscally responsible as can be, yet have fallen victim to circumstances. That's the situation Ward and Coleman are in. They're working to make their peace with a potential change of plans.

As Ward says, "We're fortunate enough to live on five acres in a great setting. It's a large house and a good place for grandkids."

He says, "I certainly do love having the kids around."

If he's ultimately forced to delay retirement, that's at least one consolation prize.

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If I pulled one of your advisers aside tomorrow and asked them to walk me through your sales process step by step, from start to finish, could they do it? Could they tell me what happens in the first appointment, what gets said, what questions get asked and exactly how a prospect moves from curious to committed?

If the answer is "probably not," you don't have a sales process — you have a sales idea. And ideas, as good as they can be, don't scale.

I want to start there, because I believe the sales process is the single highest-leverage investment you can make in your business. Not a new CRM. Not a different marketing strategy. A documented, repeatable, trainable process for how you help people make one of the most important decisions of their lives.

Why systematizing your process changes everything

Here's the thing about a systematized process: It gives you data, and data gives you power.

When you can map out every stage of your sales process — first appointment, discovery, presentation, follow-up and close — you can start to see exactly where people fall off.

Maybe your first appointments are strong, but your second appointments are where you lose momentum. Maybe your close rate is great, but prospects are taking 90 days to convert when they should be taking 30. You'll never know until the process is written down.

I've talked to hundreds of top advisers, and the ones who are scaling, really scaling, aren't the ones with the most charisma in the room. They're the ones who've taken what they do naturally and turned it into something teachable.

Small hinges swing big doors. A 5% improvement in your conversion rate, compounded over a full year of appointments, is the difference between a good year and a great one.

Start with a recording

So, how do you build a process if you don't have one documented? Start with a recording.

With your client's permission, record three to five of your appointments. Then, upload those recordings into an artificial intelligence tool. Ask it to do a few things:

• Identify the structure of your conversation
• Flag where transitions happen
• Note the questions you ask and when you ask them
• Outline what you're communicating in each phase of the meeting

What you'll get back is a mirror. You'll see your process as it actually exists, not how you think it exists. And from that mirror, you can start to build something real — a written framework with defined stages, key questions, value statements and transition language. A process that lives outside your head.

Once it's documented, it's trainable. Now, when you hire an adviser, you're handing them a playbook of your sales process instead of hoping they pick it up through osmosis. That is how you scale.

Use AI as your personal sales coach

For those of you who already have a process — maybe you've been in this business for 15 years — you know your steps and your language. Here's how AI can still level you up.

Open your AI tool of choice and prompt it like this:

"I want you to act as an expert sales trainer who specializes in financial services and complex consultative selling. Here is my current sales process. Review each step and tell me: Where is there friction? What objections am I not addressing early enough? What questions should I be asking that I'm not? How can I tighten my value proposition?"

The feedback you get will be genuinely useful. AI has absorbed more sales methodology, psychology and process design than any single coach you could hire. Used this way, it's like having a world-class sales trainer on call, available whenever you have 30 minutes and a willingness to improve.

Then try something it suggests. Not 10 things — just one. Test a new discovery question. Adjust your transition into the second meeting. Refine how you open the closing conversation. See what moves the needle. If it works, bake it into your process permanently.

Remember why the process matters

I want to say something that I think gets lost in all the talk about conversion rates and close ratios: This is really about helping people.

Sales is a noble profession. I believe that in my innermost being.

Think about what you're actually doing when you sit across from a prospect. Most people, given the choice, will not make a decision. They will procrastinate, defer and wait until "the right time." They'll let inertia decide for them. They'll reach retirement having never truly planned for it, not because they didn't have the resources, but because no one ever pushed them to act.

You are that person. You are the one who sits down with someone, helps them see what their future looks like and then helps them do something about it. The work you do to improve your process, to sharpen your questions, to get better at guiding people through a decision — that work directly translates into better retirements for real people.

Believe in what you do. Work hard at it. Don't apologize for being good at converting people, because converting them means they're supported. It means they'll have a plan when the market drops. It means their spouse won't be left scrambling.

The best salespeople I've ever met aren't the slickest — they're the ones who believe most deeply that their clients need what they're offering and have refined their ability to communicate that clearly.

A challenge for you

Record your next three appointments and upload them into AI. Build or refine your documented process, then share it with your team and train against it. If you already have a strong process, spend 30 minutes with AI acting as your sales coach and identify one thing to improve. Just one.

The advisers who will look back on 2026 as a breakout year won't be the ones who worked harder. They're the ones who worked on the right things — and a systematized sales process is one of the right things.

You help people enjoy their retirement. What you do matters. Do it with intention, do it with excellence and do it with the confidence that comes from knowing your process cold.

Make this the year you build something that scales.

Advisors Excel's mission is simple yet profound: to help good advisers become great business owners while enabling their clients to enjoy the retirement of their dreams.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Your business is going to spend more on AI this year. Three-quarters of finance leaders raised technology budgets for 2026, nearly half of them by 10% or more, and financial services firms led every other sector with increases around 15%.

The decision to spend is made. The harder question is the one your budget process is not built to answer: How do you forecast a cost that changes based on how your people use a tool?

Most firms get this wrong in two specific ways. Let's review both before you build your AI budget.

Mistake one: Budgeting AI as a fixed cost

You are used to software that costs the same every month. You buy a number of seats, you pay a flat fee, and the bill is the bill.

AI does not work that way. The cost tracks consumption, not headcount. Two advisers on the same license can generate wildly different bills because one runs long reports through the tool all day, and the other asks it a question twice a week.

This breaks the annual budget. You cannot set one number in January and hold it, because usage climbs as your people get better at the AI tool and find more uses for it.

A fixed line item guarantees one of two outcomes. You overfund it and waste capital you could have deployed elsewhere, or you underfund it and face an overage conversation in a near future quarter.

Treat AI the way you treat a variable operating cost, not a license. Build it as a range with a floor and a ceiling, then forecast on a rolling basis and revise quarterly. A firm running this as a static annual figure is budgeting a variable cost with a fixed budget, and the budget will lose.

Mistake two: Budgeting only the token bill

The number the vendor invoices you is the visible part of the cost. It is not the whole cost.

Every AI workflow carries expenses that never appear on the vendor's bill, namely the human in the loop.

• Someone must review the output before it reaches a client, because a fiduciary cannot send unreviewed AI work product to the people who trust the firm with their money
• Someone must train staff on the tool
• Someone must maintain the governance, the acceptable use policy, the compliance records that an examiner will ask for

These are real costs, they scale with adoption, and they belong in the same budget line as the tokens.

This is why ownership matters as much as the number. Research on AI return shows that firms where technology teams own AI spend alone capture less value than firms where finance and compliance share the decision.

The token bill is a technology expense (although it should be a business expense). The review time and the regulatory exposure are not. Budget them together or you will underfund the part that keeps you out of trouble.

Budget against honest return, not the promise

Here is the number that should govern how aggressively you fund this. Less than 1% of executives report AI returns of 20% or greater, and a majority report returns in the range of 1% to 5%.

Meanwhile, Gartner expects 30% of generative AI projects to be abandoned after the proof of concept stage. The spending is real. The proven return, for most firms, is not yet.

This does not argue for sitting out. It argues for funding against measured outcomes rather than the vendor's promise. Tie each AI budget line to a specific result you can measure, such as hours saved in a named workflow or a reduction in a particular operational cost.

Fund the use cases that clear that bar and reject the ones that do not. The firms that win the next three years will be the ones that fund AI where the business case is strong and measurable and refuse to fund it anywhere else.

How to build the number

Start with a pilot you meter. Run one real workflow through the tool for a full month and read the bill. That gives you a true cost per task, which is the only honest input to a forecast. Multiply by realistic adoption, not best-case adoption. Then add the costs the vendor never invoices: The time to review output, the time to train staff, the work to maintain governance.

Build the result as a range. Set a floor that covers committed usage and a ceiling that absorbs the growth you know is coming. Attach a pay-as-you-go overflow so that crossing the ceiling slows you down rather than cutting off a workflow your advisers now depend on. Then revisit the whole figure every quarter, because the underlying prices are moving and your usage is moving faster.

AI is now a permanent line in your operating budget. Treat it like one. Forecast it like a variable cost, fund it against measured return, and revise it on a schedule. The CFO who does this will deploy capital where it earns its keep. The CFO who sets a fixed number in January will spend the year explaining variances.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

If AI is helping financial advisers save time and become more efficient, investors should be asking a simple question: Who benefits from that efficiency?

What if your financial adviser suddenly started taking on twice as many clients? A year ago, that question would have sounded hypothetical. Today, it's entirely plausible.

Artificial intelligence is rapidly changing the economics of the financial advice business. The biggest brokerage firms and financial institutions on Wall Street are openly celebrating how AI will help them cut costs, increase adviser productivity and onboard more clients without adding staff.

According to Bloomberg, JPMorgan CEO Jamie Dimon said the bank's roughly $2 billion annual investment in AI is already producing billions in benefits and cost savings.

Business Insider reported that Dimon pointed to AI-driven savings from reduced headcount, productivity gains and operational efficiencies, while describing the benefits as only "the tip of the iceberg."

What's missing

Conspicuously absent from this reporting was any meaningful discussion about how AI would improve the client experience. That's where the conversation stops being about technology and starts being about ethics.

That became clear to me during a recent podcast conversation with Jeff George, CFA and founder of TAO Financial, an independent fee-only fiduciary adviser who is a member of my Wealthramp network. Like many advisers, Jeff has begun integrating AI into his practice.

Jeff explained he's using AI to help organize research, prepare for client meetings and capture notes during conversations (without sharing personal information).

The note-taking capability, in particular, has changed how he works with clients. Instead of dividing his attention between listening and documenting, he can focus entirely on the conversation and review a detailed record afterward.

That's a meaningful improvement in the client experience because the efficiency allows him more face time with clients.

What Jeff does not do is allow AI to participate in the part of the process clients are paying him for.

"I don't allow AI to influence anything that requires independent judgment," he told me. More telling was what came next: "I believe that clients are hiring me for my advice and that they want my brain. And if I'm using AI to build financial plans, then what are they really paying for?"

Jeff's guardrails are surprisingly straightforward:

• He won't allow AI to recommend portfolio changes, determine withdrawal strategies or make planning recommendations that require professional judgment
• He won't upload client information into public AI tools
• He won't accept AI-generated conclusions without verifying the underlying sources himself
• He won't present AI-generated output to a client as if it were his own analysis

Those guardrails aren't just a reflection of Jeff's approach to AI. They highlight a much bigger issue for investors.

Too much information can overwhelm

Most people who reach out to me to find fiduciary advisers aren't suffering from a lack of information. If anything, they're overwhelmed by it. They've read articles, listened to podcasts, watched YouTube videos and increasingly experimented with AI themselves.

What they still don't know is whether they can afford to retire, whether they're taking too much risk, whether helping an adult child will jeopardize their own future or whether they're making a costly mistake they can't see.

Those are judgment problems that require decisions to be made with full context.

Two investors can have identical portfolios, identical incomes and identical account balances and still need completely different advice because they're solving different life problems. One might be caring for an aging parent.

Another could be supporting grandchildren. One might be terrified of running out of money. Another could need permission to spend more freely. The facts might be the same. The advice should not be.

This is where I think the AI conversation sometimes goes off track.

People often ask whether AI will replace financial advisers. Increasingly, I hear a different version of the question: If consumers have access to the same AI tools, why hire an adviser at all?

It's a fair question.

Consumers can absolutely use AI to become better-informed investors. They can ask smarter questions, learn unfamiliar concepts, compare strategies, explore retirement scenarios and organize information far more efficiently than ever before. Used thoughtfully, AI can be a powerful financial education tool.

But information and advice aren't the same thing.

Jeff described that tension perfectly. Used appropriately, AI can handle the blocking and tackling of running an advisory practice — organizing information, managing workflows, documenting conversations and performing preliminary research.

That frees advisers to spend more time doing work that actually requires experience, context and judgment.

But he also acknowledged the slippery slope. At some point, every adviser will face a choice between using AI to serve clients better and using AI to serve more clients. Those aren't necessarily the same thing.

That's why I believe consumers need to ask a different set of questions. Instead of asking whether an adviser uses AI, find out how you benefit from it. Ask:

• What safeguards are in place to ensure AI supports rather than replaces personalized advice?
• Is confidential information is ever entered into public AI systems?
• What decisions are never delegated to technology?
• How will the adviser's use of AI improve your experience as a client?

This should become part of your adviser vetting process, because their answers will reveal where most of the benefits of AI are flowing — to you or to their firm.

Financial advice has always been an industry where consumers had to look beyond marketing claims to understand what they were really buying. AI doesn't change that reality. If anything, it makes the distinction between outstanding fiduciary advisers and sales-driven advisers easier to see.

The advisers who stand out in the next decade won't necessarily be the ones using the most sophisticated technology. They'll be the ones who can clearly explain how they're using it, why they're using it and where they draw the line.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

What does a cutting-edge artificial intelligence data center have in common with a natural gas pipeline built decades ago?

More than most investors realize.

The race to build AI may be dominated by headlines about chips, software and trillion-dollar technology companies, but the infrastructure supporting that growth could create opportunities in a much less glamorous corner of the market.

About three years ago, I wrote my first article for Kiplinger. It focused on pipeline companies, which many investors expected would become obsolete from the global transition toward renewable energy.

I argued that the market was underestimating the durability of energy demand, particularly for natural gas, and the importance of the infrastructure required to transport and process it.

That thesis has not only held up — it may have become even more compelling.

Opportunities in the pipeline

AI is driving an enormous increase in electricity demand as data centers are built across the country. While renewable energy will undoubtedly play a critical role in meeting future needs, natural gas remains one of the most reliable and readily available sources of around-the-clock power.

As a result, many utilities have significantly increased their expectations for future natural gas power generation.

This creates an interesting opportunity for pipeline operators. Many of the companies that own the existing network of natural gas pipelines possess assets that would be incredibly difficult, expensive and time-consuming to replicate.

The AI revolution may be driven by cutting-edge technology, but it still depends on physical infrastructure built over decades.

Investors who experienced the painful collapse of the MLP sector during the last energy downturn may also be surprised to learn how much the industry has changed.

The old model of aggressively issuing debt and equity to finance growth has largely been replaced by a more disciplined approach focused on stronger balance sheets, internally funded growth, free cash flow generation and returning capital to shareholders.

This evolution is particularly important because it changes the way investors should think about the sector. Many people still associate energy investing with a simple bet on oil and natural gas prices.

However, many midstream businesses generate cash flow based on the volume of energy moving through their systems, often under long-term contracts, rather than the daily swings of commodity prices.

Investing in the age of AI

This idea is consistent with a broader framework I recently discussed in a Stansberry Asset Management webinar on investing in the age of AI: The best opportunities may not only come from the companies creating new technologies, but also from businesses with durable assets, low risk of obsolescence and an essential role in supporting the future economy.

For investors willing to roll up their sleeves, individual pipeline companies may present attractive opportunities. However, selecting the right exposure requires evaluating factors such as asset quality, growth opportunities, balance sheet strength and valuation.

Many investors may therefore prefer a diversified fund or to work with a professional investment manager such as Stansberry Asset Management (where I am the deputy chief investment officer) that can determine how best to incorporate this opportunity into a broader financial plan.

When I first wrote about pipeline companies for Kiplinger, the question was whether the world would still need them decades into the future. Today, that answer appears clearer than ever.

The AI investment nobody is talking about may not be the technology itself, but the infrastructure required to power it.

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It's not a secret that AI adoption is becoming increasingly commonplace in Corporate America. But it's not just giant corporations that are using it. A 2026 Intuit QuickBooks survey (PDF) found that 77% of small and midsize businesses now use AI regularly, up from 48% two years ago.

If you own a small business, you may be looking to increasingly lean on AI tools to improve productivity and save on costs. In fact, the same QuickBooks survey found that 78% of US respondents reported productivity gains from AI use, and 42% reported revenue gains. For large companies, a PwC study found that investing at least 1.6% of revenue in AI tools resulted in 9.5% growth (as measured in EBITDA). Moreover, AI can help create documented workflows and efficiencies that can give you a higher exit price when you're ready to sell up and retire.

But what if those tools are making some of your employees' tasks obsolete?

On a scale of 1-5, which of the following describes your current views of AI's impact on your productivity? (Asked of U.S. small businesses.)

Letting employees go is a gut-wrenching decision for any small business owner. But when your personal finances are at stake, sometimes you may need to make hard choices.

If you're a business owner who's looking to power through for a few more years and sell your business to fund your retirement, you need your company to be profitable and competitive. That means shedding unnecessary costs and using technology to your advantage. Here's how to reconcile the financial side of the equation with the moral and emotional side.

Look at AI as a time-saver more than anything else

AI may be able to take over some of the tasks your employees handle now. But that doesn't mean those employees suddenly lose all of their value.

Paul Carlson, CPA and managing partner at Law Firm Velocity, a company that provides virtual CFO and financial services to law firms across America, says, "You don’t want to make decisions out of guilt and keep carrying payroll that no longer makes financial sense for the business."

He explains, however, that just because AI is saving you time doesn't mean your employees with years of business knowledge and experience are suddenly obsolete.

"What helps you make a more mindful decision is to first see whether the freed-up time can actually improve some other aspect of your business," Carlson says. Those aspects could be things AI can't handle, such as strategic decisions that require more human intervention and judgment.

Carlson says that discovering the time-saving power of AI could position you to make better use of your employees' skills rather than letting them go.

"In most small businesses, your employees will most certainly end up wearing multiple hats over time. So even if AI suddenly saves someone five or six hours a week, that doesn’t necessitate that the employee is no longer able to play a part, especially given the kind of context they have about what works for your business and what doesn't," he explains.

Carlson also points out that if you're running a lean operation, you may not be tracking the various ways your employees are contributing. Before letting them go, it pays to take a closer look.

"Some employees are integral when it comes to catching mistakes," he says. "Others are great at answering questions nobody else has time to deal with, or take great pride when following up with clients. All those elements may have had a big role to play in your company’s reputation and how satisfied clients are with you."

E.J. Simonsen, Founder & Finance Advisor at EIDLexit, agrees. His best advice? "Replace tasks, not people."

"Routine administrative labor can be handled by AI," he says. "Use the savings of time to transition employees into higher value endeavors such as customer service, business development, process improvement, or client retention. Those domains are often higher impact to revenue and significantly harder to automate. This enables you to be competitive while still investing in your team."

Proper AI adoption could make your business more valuable

If retirement is on the horizon and you're within 10 years of an exit plan, you need a sound strategy that enables your business to maintain its edge without blowing money on unnecessary costs.

Kevin Williams, founder of Ascend AI, advises C-suite executives and small business owners on AI adoption, governance, and workforce readiness. And he says that given your timeline, you have a prime opportunity to use AI in a way that could make your business more valuable without shedding headcount.

"Companies where AI is used strategically and where the team knows how to leverage it fetch a higher price," he insists. "Such companies are viewed as mature, where things work efficiently. Buyers pay a premium for that."

Williams also says, "Using AI to increase productivity of each employee by 20-30% and thus build a lean and competent organization that is highly valued by a potential buyer [several] years down the road — that's how to retire successfully."

Simonsen says that ultimately, a business that runs well and has good and skilled people will generally be worth more. On the flip side, if AI adoption makes a business feel cold, automated, or robotic, client retention might drop.

"Balancing compassion and business decisions is part of establishing a better company," he says.

Of course, successfully implementing AI requires an investment. And training employees to use it could take time away from daily operations while your staff gets up to speed. But if you're willing to sacrifice some short-term gains, you may find that AI boosts your company's profitability in the long run and puts you in a stronger position once you're ready to sell.

It's also important to be transparent with your employees about how you're looking to integrate AI. Nothing hurts employee morale like the fear of being replaced by a machine. Emphasize that you're adopting AI tools to make their jobs easier, not to replace them.

Take guilt out of the equation

It's natural to feel bad about the idea of letting hard-working employees go. But if you use AI the right way, you may not have to.

"If you feel guilty about AI, then this is because you miss the point entirely," Williams says. "Guilt doesn't arise from using AI technology. It comes from the choice you made [regarding] AI use."

Of course, you may come to the realization that one or two roles at your company are, in fact, obsolete in the wake of AI, and that you can't justify the cost of labor. In that case, it's important to do your best to ethically offboard those employees.

If you can afford to be generous with severance, it could ease the financial blow for those impacted while helping you sleep better at night. Be empathetic but pragmatic.

But all told, Williams says, using AI to empower your employees rather than replace them could set you up for a lot more financial success. And that way, you can forge forward with your personal financial plans without the remorse that might come with destroying other people's livelihoods.

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AI has already affected how we learn, work and govern ourselves much faster than research, regulation or nonprofits can keep pace.

While businesses and governments scramble to respond, philanthropists hold a distinct and underutilized advantage: The flexibility to fund what others won't, invest where we still need evidence and work across sectors without commercial pressure.

Here is how to leverage your advantages as a donor.

1. Sharpen your nonprofit due diligence

AI-generated misinformation makes vetting organizations harder than ever. Donors can raise their standards by:

• Identifying ratings from Charity Navigator, the BBB Wise Giving Alliance and GuideStar's Seals of Transparency before committing funds
• Visiting local organizations in person — no rating system replaces direct observation of a program in action
• Asking nonprofits you regularly support how they manage AI-related data risks before your next significant gift conversation

2. Fund nonprofit AI capacity — not just programs

Most nonprofits use AI primarily for basic productivity: Drafting emails, summarizing meetings, writing grant applications. The real leverage lies in mission-critical AI deployment — but getting there requires infrastructure most nonprofits lack, and the risks of moving forward without it remain severe.

Unlike corporations, nonprofits face the same cybersecurity vulnerabilities with far fewer resources. They routinely manage donor financial data, personally identifiable information, health records and confidential beneficiary files.

Large language models like ChatGPT and Claude collect and store user data indefinitely — meaning a nonprofit that uploads sensitive files to an AI platform may lose ownership of that data entirely.

Cybercriminals also actively use AI to make attacks harder to detect. A single breach can devastate fundraising, damage community trust and trigger regulatory consequences under state, federal or international privacy law.

To empower nonprofits to function effectively with AI, you may:

• Fund general technology budgets. IT infrastructure upgrades remain chronically underfunded, yet are essential for safe and effective AI use. Consider directing unrestricted gifts specifically toward this gap.
• Sponsor AI education and policy development. Nonprofit leaders identify four priorities: Staff training on AI fundamentals, dedicated software funding, technical development opportunities and guidance on how AI affects the communities they serve.

As a result, you can free up charities to make truly transformational changes. For instance, the MacArthur Foundation's recent $100 million award funded an AI-driven global infectious disease surveillance system, a model for what becomes possible with the right infrastructure in place.

3. Support publicly available AI research

It has become clear that AI will affect jobs across every sector — augmenting some roles, restructuring others and eliminating others. Yet workforce impact data remains fragmented, with no uniform standards for measuring AI exposure, adoption or economic effect across sectors.

Educators and employers commonly agree that student preparation for an AI-embedded future entails independent decision-making, problem-solving and media literacy, rather than task completion. In essence, students need to be taught how to think, not what to think.

However, educators have had to make high-stakes technology adoption decisions with insufficient evidence.

As labor markets shift, demand will rise for portable access to healthcare, education and job retraining.

For instance, potential ideas such as portable benefits, decoupling health insurance and retirement savings from traditional employment, require rigorous, publicly available research to move from concept to viable policy.

As a result, AI research remains "in the first inning."

Donors can accelerate the learning curve to keep up with industrial changes by:

• Funding research based on multiple perspectives, including those of teachers, parents and students, on AI's impact on learning
• Prioritize studies that remain open to the public, so other researchers can replicate and build on findings
• Support workforce transition research, particularly around portable benefits and safety-net access for workers in AI-disrupted industries

4. Strengthen civic voices in developing AI policy

Most workers and communities recognize the efficiencies offered by AI, understand their benefits and don't want to eliminate them.

Instead, they simply want a seat at the table in deciding how AI applies to them. In fact, more than half of U.S. adults (55%) say they want greater control over AI in their lives.

That demand extends to transparency about AI's environmental footprint and corporate accountability on data privacy.

Philanthropy has a direct role in amplifying a community's civic voice by:

• Funding local and independent journalism to ensure communities receive accurate, accessible information about AI's local implications
• Supporting civic participation initiatives that bring residents, not just industries, into community-level AI policy and land-use decisions

5. Align your financial investments with your philanthropic goals

Ideally, your investment portfolio and your philanthropic priorities would reinforce, and not negate, each other. Accounting for environmental, social and governance factors may improve long-term returns by unlocking value and achieving resilient, long-term investment success.

You can adjust your investment and philanthropy alignment by:

• Reviewing your current AI-related holdings and their impacts in the areas that you care about most as a philanthropist
• Consulting with your investment adviser on frameworks for considering environmental, social and corporate governance factors

6. Team up with other donors

AI's societal scale exceeds what any single donor can address. Philanthropists who coordinate with peers can multiply their impact, reduce duplication and gain access to shared due diligence.

In collaborating with other donors, you may:

• Explore foundation coalitions like Humanity AI to review their vetted grantee list and potentially identify organizations aligned with your priorities
• Join or convene a donor working group focused on AI's impact in your areas of giving — education, workforce, health or civic participation

The philanthropists who move now can help influence AI for good. In funding research, nonprofit capacity and broad civic engagement and working with other donors, you can advance the positive impact of AI and mitigate its challenges for decades ahead.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

A young investor today wakes up to a TikTok video on private credit, asks a generative AI tool to draft a retirement plan over breakfast, scrolls through podcasts comparing crypto custodians on the commute and fields a robo-adviser's portfolio recommendation before lunch.

Information about money has never been cheaper to produce, easier to access or harder to evaluate. However, despite the ubiquity of investment information, human advisers remain the single most trusted source of guidance for young investors today.

The role of traditional investment advice in an age of digital communication is a central tension in the new Next-Gen Investors report from CFA Institute, which draws from a survey of more than 2,400 mass-affluent and high-net-worth investors in six major wealth markets around the world.

Instead of reading this as nostalgia for a fading model, consider how trust works in a saturated information environment. When advice is everywhere, the question is no longer who has the answer, but who can be trusted to guide choices among many possible answers.

Younger clients are looking for a curator and collaborator, and the advisers who recognize that will own the next generation of relationships.

How advisers can stay relevant

What makes young investors different is how they verify trust. Older investors tended to define trustworthiness primarily through the relationship itself, with years of personal history, in-person meetings, and continuity across family generations. Gen Z and Millennial investors still want that personability, but they expect it alongside measurable, professional indicators.

Our research shows young investors place greater weight on professional credentials, transparency around conflicts of interest, data security and verifiable performance against benchmarks.

These markers are particularly valuable in a world ripe with mass-produced AI advice. Professional credentials, for example, are one of the few public proofs that a person, not a machine, has demonstrated domain knowledge and expertise.

This measurable trust is what advisers can lean into to stay relevant. In our survey, approximately one third of Gen Z and Millennials already use generative AI to learn about investing. Generative tools will keep getting better at producing fluent-sounding advice, but fluency is not judgment.

Cut through the hype

Seasoned advisers bring years of seeing market cycles, regulatory changes, behavioral patterns and the outcomes of decisions that looked obvious at the time. That experience is exactly what cuts through hype. An AI tool may produce responses that sound confident, but it cannot replace competence.

For advisers, this reframes the scope of their work. Professionals are no longer the primary gatekeeper for investing. Clients now have access to an abundance of information. Instead, the job is to serve as a curator, validator and translator of an overwhelming digital landscape.

In some ways, that is a more demanding role, yet a more durable one. It means being fluent in the latest products your clients are reading about, including the ones you would not personally recommend, so you can have an informed conversation rather than a defensive one, and being ready to interpret a viral video or an output a client copied out of a chatbot.

Younger clients are not going to stop consuming content, but they want an expert whose true value lies in human judgment.

Communicating that value is now part of the job. Younger clients will not assume seasoned judgment is in the room but will look for evidence of it.

Treat credentials, professional experience and past performance as strategic assets that are clearly communicated to current and future clients.

Document conflict-of-interest policies in plain language and make them client-readable.

Show the work behind a recommendation, including supporting evidence, not just the conclusion.

At the same time, AI can be a useful tool to communicate the value proposition of adviser judgement. Used well, it removes the friction that prevents advisers from being successful curators and collaborators.

AI can help with drafting first-pass communications, summarizing trends, preparing for meetings and scaling personalized check-ins.

Nearly 70% of Gen Z and Millennial investors in our study who use a paid financial professional interact with their adviser at least monthly. That cadence is difficult to sustain without technology, but underlying those interactions is the adviser's expertise and judgment orchestrating those communications.

Voice of reason

But the deeper reason younger clients want a human adviser is that the world has become a noisy place, and navigating the signals and products can be overwhelming and lead to rash decision-making.

Over half of Gen Z and Millennial investors in our research have already made at least one investment driven purely by fear of missing out (FOMO), most often in cryptocurrency.

As markets continue to show volatility, and as new investment opportunities emerge, the adviser's role is to be the person on the other end of the line when the next market dip arrives, the next can't-miss asset surfaces, or the noise of information gets too loud.

The point is not to chase every trend or reflexively dismiss new products or opportunities, but to be a voice of reason and stability. A credentialed, experienced professional who can keep clients aligned to their long-term goals and strategies; steadfastness becomes even more valuable in a noisy environment.

The advisers and firms who successfully adapt to the next generation will not approach AI as a threat, nor as a replacement for the adviser-client relationship.

They will be the ones who use technology to amplify their reach, and focus on their human qualities of judgment, accountability, ethical stewardship and demonstrated experience, which no algorithm can fully capture.

Genevieve Hayman, PhD, and Ryan Munson are co-authors of the CFA Institute Research and Policy Center report Next-Gen Investors: A Guide for Wealth Managers and Financial Advisers.

Genevieve Hayman is a senior manager of macrosystems and foresight at CFA Institute. Her research focuses on pensions and retirement security, complex systems, cognitive science and the long-term forces shaping global finance. In her role, she develops structured, long-horizon scenario frameworks that examine how technological, economic and regulatory shifts may reshape financial markets, institutional behavior and professional norms. She also contributes to early-warning frameworks and cross-pillar integration across CFA Institute's research agenda.

Ryan Munson is a research manager at CFA Institute. His research focuses on pensions and the future of finance, exploring how extra-financial factors impact the investment industry and investment professionals. Ryan serves on the advisory board for the Mercer CFA Institute Global Pension Index. He is the author of several CFA Institute publications, including the Future State of the Investment Industry, the Future of Work in Investment Management series and the CFA Institute Investor Trust series.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

SpaceX, OpenAI and Anthropic sit at the center of the artificial intelligence and space infrastructure boom.

All three are preparing, or are widely reported to be preparing, for public listings at valuations that could collectively exceed $3 trillion.

These are not just big IPOs. They may become turning points for the economy and for investors who are already retired or nearing retirement.

After several slow years for new listings, the IPO market has roared back, led by companies tied directly to AI. Chipmakers, data platforms and now foundation-model companies are drawing intense investor demand and extraordinary price tags.

SpaceX is reportedly targeting a valuation of roughly $1.75 trillion in what could become the largest U.S. stock market debut on record.

OpenAI, the company behind ChatGPT, is reportedly preparing to file for a U.S. IPO and was recently valued at roughly $852 billion.

Anthropic, creator of Claude, has already filed confidentially for an IPO and recently raised capital at a reported $965 billion post-money valuation.

In plain English, public markets may soon absorb several of the largest technology offerings in history, all clustered around one theme: The belief that AI will transform the economy.

Why this matters

AI is no longer just a technology story. It is increasingly an economic one.

Stanford's 2025 AI Index estimated that global corporate AI investment reached $252.3 billion in 2024, with private investment and merger activity still rising. That level of spending helps explain why AI has become one of the dominant stories behind recent market optimism.

But there is a risk. A small group of large technology and AI-linked companies, known as the Magnificent 7, already accounts for a disproportionate share of stock market leadership.

If SpaceX, OpenAI and Anthropic enter the public markets at enormous valuations, that concentration could grow even more.

For investors, concentration cuts both ways. If AI leaders continue to grow into their valuations, broad index funds may benefit.

But if expectations reset, because of slower adoption, regulatory pressure, profit disappointments or capital spending concerns, the same broad index funds could feel the downside.

This is especially important for retirees. When you are still working, market pullbacks are painful but often recoverable with time and new contributions.

In retirement, the math changes. If you are taking withdrawals during a market decline, you may be forced to sell shares when prices are depressed.

That is sequence-of-returns risk, and it becomes more dangerous when market gains are narrow and concentrated.

The emotional pull

The hardest part of this moment is not the math. It is the emotion.

Many investors remember missing earlier waves, such as the internet, smartphones, cloud computing or Nvidia (NVDA). When financial headlines start talking about the "most anticipated IPOs" and trillion-dollar valuations, the temptation is to chase the next big thing before everyone else gets in.

That temptation can be costly. Some of these companies may become extraordinary long-term businesses. But buying a great company at the wrong price can still produce poor returns. The bigger the valuation at the starting line, the more future growth may already be priced in.

For retirees, that matters. You do not have the same margin for error as a 30-year-old investor with decades of income ahead. A speculative position that drops sharply can do more than hurt performance. It can disrupt income planning, withdrawal strategy and peace of mind.

What smart retirees can do

The goal is not to ignore AI. AI is real, and it may help drive the next decade of growth. The goal is to avoid letting excitement replace discipline.

First, review your diversification. Look under the hood of your stocks, mutual funds and ETFs.

How much of your equity exposure is tied to a handful of mega-cap technology and AI-linked names? You may already own more of this theme than you realize.

Second, separate the story from the strategy. The story around these IPOs is compelling: Revolutionary technology, visionary founders and massive addressable markets.

But a retirement strategy should be built around cash-flow needs, inflation, longevity risk, taxes and risk tolerance, not headlines.

Third, use AI as a planning tool, not a lottery ticket. AI may improve portfolio monitoring, tax planning, income modeling and risk management.

For retirees, that may be the more productive use of the technology than speculating on the hottest new AI stock.

Fourth, think in scenarios, not predictions. Ask two simple questions:

• If AI mega-caps keep driving markets higher, am I positioned to participate?
• If they stumble, can I still meet my spending needs?

A good retirement plan should work across a range of outcomes, not just the optimistic one.

Finally, revisit your withdrawal and risk policies. Periods of market enthusiasm are a good time to make sure your cash buffer, income plan and equity exposure still fit your real life.

The bottom line

The coming wave of AI-driven mega-IPOs is a sign that we are living through a genuine technological transition and a period of elevated market optimism. The valuations being discussed for SpaceX, OpenAI and Anthropic show that investors are willing to pay today for a future where AI reshapes productivity, software, defense, healthcare and transportation.

For retirees, the goal is not to bet your nest egg on that future. It is to recognize that a growing share of your portfolio may be influenced by a small cluster of AI-centric giants, then plan accordingly.

AI may help power the next decade of growth, but a disciplined retirement plan is still what turns that growth into reliable income.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Drive through eastern Loudoun County, Virginia, and you will quickly understand why some parts of the area are often referred to as "Data Center Alley."

Massive, windowless gray cement structures rise up behind fences and security gates, while cranes loom over roads once lined with trees, now covered in mud from construction traffic, working to make way for yet another data center.

This mixed suburban/rural area is now home to the world’s largest concentration of data centers. Around 200 facilities are currently operating in Loudoun alone, with more planned, and they handle over one-third of the world’s daily internet traffic.

While supporters argue these centers are vital to the digital economy, many residents — not only in Virginia but across the United States — are concerned about their rapid expansion, energy and water use, and broader environmental impact.

Critics also highlight that these facilities often create fewer permanent jobs compared to the tax incentives they receive. As tensions grow, the question becomes: where do residents and lawmakers go from here?

The great data center debate

Data centers are specialized facilities that house a variety of computing components, including servers, networking equipment, and extensive drives.

Their prevalence has increased in recent years, as every time someone streams a movie, stores photos, shops online, uses social media, or interacts with AI chatbots, information is processed through these centers worldwide.

There are now reportedly around 4,000 data centers in the U.S., which some see as a good thing, helping create jobs and generate revenue.

But…data centers place significant demands on local infrastructure.

• Modern data center campuses can span dozens or even hundreds of acres and often require new power lines, substations, roads, and other infrastructure.
• Many consume significant amounts of electricity. (Just a few years ago, data centers accounted for an estimated 4% of total electricity use in the United States. By 2028, that figure is expected to climb to as high as 12%.)
• Data centers also typically rely on large diesel-powered backup generators to ensure uninterrupted operations during power outages, which raises concerns about local air quality in some communities. (According to the U.S. Environmental Protection Agency, diesel exhaust from backup generators contains fine particulate matter and nitrogen oxides that are associated with respiratory issues like asthma.)

Notably, data centers and water have emerged as another point of contention.

Depending on the design and cooling technology, large facilities can consume hundreds of thousands of gallons of water per day to cool server racks. Some large campuses reportedly use volumes comparable to those of a small town, raising sustainability questions in some communities.

Still, states and local governments across the country have spent years competing to attract data center development, often by offering generous tax incentives.

Data center tax exemptions

In recent years, 38 states have offered generous incentives, including sales tax exemptions on servers and equipment and property tax reductions, to win a larger share of the industry's explosive growth.

Increasingly, however, several of those states are facing backlash not just from residents but also from some lawmakers.

As a result, some are moving toward requiring greater transparency, shifting infrastructure costs onto developers, reexamining tax incentives, or studying the industry's impact on electricity and water supplies and local communities.

Some examples:

Illinois: Late last week, Gov. JB Pritzker directed the state's Department of Commerce to completely halt the processing of all new data center tax exemptions starting July 1.

"Illinois has an opportunity to continue leading in technological innovation and economic growth, but we also have a responsibility to protect working families and local communities as the data center industry rapidly expands," Pritzker stated in a release.

Ohio: In May, Ohio Gov. Mike DeWine ordered the state’s Tax Credit Authority to freeze all pending and new data center sales tax exemption requests. The halt came after a state report revealed that the exemption cost Ohio $1.5 billion in 2025 alone.

In a release regarding the issue, DeWine wrote, “I fully support the Ohio General Assembly's work to study the issue and bring forward facts about data centers, including the local benefits to communities when tax exemptions are granted.”

Georgia: Lawmakers in the Peach State are moving to phase out data center tax suspensions after a state audit revealed the exemptions will cost a projected $2.5 billion this year.

Data centers in Virginia: What’s happening

In Virginia, lawmakers in the Senate want to let a multibillion-dollar annual data center tax exemption expire, while the Virginia House is reportedly trying to tie any remaining tax breaks to strict environmental and clean-energy compliance rules.

According to the Commonwealth’s tax disclosures, the existing data-center sales-tax exemption in the Old Dominion state cost an estimated $1.6 billion last fiscal year.

That massive exemption and the growing backlash over the more than 600 data centers already in the Commonwealth are sticking points in a budget process that must be completed by the end of June.

At the same time, in some other states, resistance to data centers has led to new legislation. (This is not an all-inclusive list.)

• In Oklahoma, Gov. Kevin Stitt signed the Data Center Consumer Ratepayer Protection Act of 2026 into law, effective July 1. The law is designed to prevent utility cost hikes for residents.
• New York lawmakers just passed the Responsible Data Center Development Act (A11560), which, once enacted, will impose a one-year moratorium on permits for new data centers of 20 megawatts or more.
• Monterey Park, California, became the first U.S. city to enact a ban on data center developments after roughly 88% of local voters approved a June 2 ballot measure.

As of June 2026, according to various online trackers, more than 25 states are either advancing data-center-related legislation or have enacted measures that address grid cots, reporting requirements, utility regulation, tax incentives, or local authority over data centers.

What about Congress? In March 2026, Sen. Bernie Sanders (I-Vt.) and Rep. Alexandria Ocasio-Cortez (D-N.Y) introduced the Artificial Intelligence Data Center Moratorium Act. The measure, which would temporarily pause new data center construction nationwide while Congress develops federal rules for AI infrastructure, hasn’t gained traction on Capitol Hill.

Are data centers bad? Bottom line

The debate over the good and not-so-good aspects of data centers shows no signs of going away.

A recent Gallup poll finds that 71% of Americans now oppose the construction of AI data centers in their local communities (with 48% strongly opposed). The pollsters note that local data center construction is more unpopular in the U.S. than building a nuclear power plant.

This “not in my backyard” sentiment is split between environmental concerns (expressed by 50% of respondents) and economic fears, e.g., higher utility bills (about 20% of respondents), according to Gallup. Pollution, negative views of AI, and quality-of-life concerns were also factors for some.

While polling data help explain national sentiment, grassroots opposition efforts highlight local concerns.

• In Hood and Hill Counties, Texas, residents hoped to block eight proposed data centers by attending town halls in large numbers, though developers are fighting back in court. A similar effort occurred in Champaign County, Illinois, leading to a moratorium to protect a crucial aquifer.
• In Sand Springs, Oklahoma, residents mobilized in response to reports that local officials had allegedly signed non-disclosure agreements to annex 827 acres of agricultural land for a tech campus.
• Residents in Box Elder County, Utah, along with Alliance for a Better Utah, have filed a lawsuit against state development agencies over a 40,000-acre AI project backed by celebrity investors. They argue it undermines local voter oversight and grants big tech unchecked control over their water, roads, and tax structure.

Meanwhile, among those polled by Gallup who favor having a data center in their communities, the most cited reason why was potential job growth.

To that end, a Brookings Institution analysis finds that while data centers do create local jobs, it is likely “fewer than advocates claim.”

Some independent estimates put the total at a few dozen to a few hundred long-term on-site positions once a given center is constructed.

Read More

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To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

When you think about Facebook, you don’t think about monthly subscription fees. Meta wants to change that with the upcoming launch of subscription plans.

Diversifying revenue makes sense for a company that makes 98% of its sales from ads. But another factor is at play: The need to cover the soaring cost of AI infrastructure. Meta is all-in on the AI race and recently raised its planned capital expenditures for the year to between $125 billion and $145 billion, mostly because of rising memory chip prices.

Meta’s sales are smaller than the other Big Tech companies that are plowing money into AI. And unlike the other three AI giants — Alphabet, Amazon and Microsoft — Meta doesn’t have a cloud computing business that sells computing to outside customers.

Meta hopes for new ways to pay for "superintelligence"

Subscriptions are part of a bigger transformation CEO Mark Zuckerberg laid out in the company’s most recent earnings call. It’s a "vision of superintelligence," Zuckerberg said during the first-quarter earnings call at the end of April. "Our goal is not just to deliver Meta AI as an assistant, but to deliver agents that can understand your goals and then work day and night to help you achieve them."

The specifics of this vision are a bit hazy, but the focus is AI agents, the autonomous tools that do multistep tasks on a computer. Zuckerberg talked about AI helping with health, education, relationships, social media content, games, and personal and career goals. He said AI agents could buy a shirt for your daughter or help researchers cure a disease.

"I think people are going to also be willing to pay a lot of money to have premium or high-compute versions" of AI that helps achieve goals, Zuckerberg said.

There aren't many details so far on the subscriptions, which were unveiled in an Instagram post by Meta's head of product. The company revealed pricing to some news outlets, including TechCrunch. The social media versions come with extra features, such as more analytics and methods to increase viewership for posts. The AI subscriptions offer the ability to do more complex tasks with higher caps on subscribers’ usage. Meta is also targeting businesses with paid AI tools that can answer customer messages, book appointments and close sales.

Meta faces an uphill battle with subscriptions

Meta subscriptions are a long shot for the consumer market. Users have gotten used to free social media, video, messaging and other features on Facebook, Instagram and WhatsApp. And the market for AI tools is fiercely competitive, as companies such as Google and OpenAI battle for consumers. It wouldn’t be surprising if Meta struggles to get the subscriptions business to a level that would be significant to its overall revenue.

But success is relative to Meta’s formidable scale. The company made $200 billion in sales last year and now has 3.5 billion people using at least one of its apps every day. With such a huge pool of potential customers to market subscriptions to, Meta could easily find millions of willing buyers, especially among dedicated content creators. Meta will likely offer the most cutting-edge AI features to paying customers, hoping to entice free users to upgrade.

Meta Subscription Plans

1. For Social Media and Messaging

• Instagram Plus: $3.99/month
• Facebook Plus: $3.99/month
• WhatsApp Plus: $2.99/month

2. For Creators and Businesses

• Meta One Essential: $14.99/month
• Meta One Advanced: $49.99/month

3. For AI Users

• Meta One Plus: $7.99/month
• Meta One Premium: $19.99/month

The challenge of tracking Meta’s AI spending ROI

One analyst asked Zuckerberg what he is watching to make sure there’s a healthy return on investment when it comes to the soaring capex spending. Zuckerberg said the focus is building a top AI model that goes head-to-head with Anthropic, Google, OpenAI and xAI. Then he said, "I mean like, I don’t think we have a precise plan for exactly how each product is going to scale month-over-month or anything like that."

The lack of specifics, tied to the exorbitant spending required to be an AI leader, is one reason some investors are concerned, even though Meta continues to point to growing ad sales as a benefit of AI.

However, part of this new AI vision fits with Meta’s tried-and-true strategy: Get users to stay longer and see more ads. Zuckerberg said AI helps Meta understand users in more detail and makes ads more effective. He also highlighted that Meta has always focused on building a huge audience first and making money later.

Meta says it has an escape hatch of sorts to avoid owning a glut of unused data center capacity. Zuckerberg says the company has flexibility to bring data centers online more slowly or reduce spending in future years. He’s even said Meta could launch a cloud computing business to rent out computing power to other companies.

Those ideas aren’t in the works yet. "Our experience so far has been that we have continued to underestimate our compute needs," said Susan Li, Meta's chief financial officer, on the earnings call. That’s mainly because Meta has aggressively rolled out free AI tools to both consumers and businesses, whether they want them or not.

This is not the first time Meta has pivoted

The transformation into an AI company, grounded by a massive social media platform, isn’t the first corporate shift. Recall how Facebook changed its name to Meta in 2021 to make a big push into the virtual reality-based metaverse, a move that hasn’t gained traction with users. That endeavor cost the company an estimated $80 billion.

It underscores Zuckerberg’s flexibility in pursuit of growth, like his abrupt shift to short-form video to compete with TikTok. That flexibility now underpins the bet on AI, his biggest one yet.

Editor's note: This story has been updated to reflect a quote is correctly attributed to Li.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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"When the robots take over, I hope they think of me fondly."

That tongue-in-cheek internet joke has turned sour with the increasing usage of artificial intelligence (AI).

Today, it's nearly impossible to click through a few pages without encountering an AI overview — a constant reminder of how much our relationship with information has shifted.

But while you might trust an automatic notetaker or suggested recipe, AI's latest trend, "vibe coding," could raise new concerns in the financial world as AI shifts from merely summarizing information to building the very tools we use to manage that data.

Vibe-coded programs are created entirely by talking to an AI assistant in natural language, like English. This approach lets anyone create an application without coding experience, which can be dangerous when unvetted apps are deployed with coding errors, security flaws, or compliance risks.

Confidential information, like tax data or account balances, could be exposed during security breaches or compliance issues, especially when those tools handle sensitive financial workflows. These risks might be even greater among retirement-aged adults, who are particularly targeted by AI tax scams, according to recent McAfee research.

So how do you know what's safely vetted by a financial professional versus produced by robots for you to consume?

From one human to another, here's how to tell the difference.

The problem with vibe coding in financial tools

Vibe coding is a way of building software in which you tell AI the high-level idea or "vibes" of what you want built, and the machine creates the program for you.

The AI does this by feeding your input into a large language model (LLM) like ChatGPT, Claude, or Gemini to translate your instructions into functional source code.

Not only is coding like this a fast and easy way to create a financial app, but it can also quickly generate retirement tax tools like IRA withdrawal optimizers and Social Security benefit calculators.

So what's the problem? Well, whereas "vibing" prioritizes speed, it often sacrifices quality and security.

• AI-generated code notoriously produces 1.7 times more coding issues, like logic errors and security vulnerabilities, than human-written code.
• This is because AI can use up to 10 times the lines of code as a trained programmer to build the same program (paywall).

But you might be thinking:

...Well, that's often easier said than done.

Maybe if you've used Adobe's attempt at "vibe coding" with Dreamweaver, you might know how easy it is to drag and drop a simple rectangle on the screen, only to discover later how much harder it is to sort through the machine-generated code when you want to change the rectangle's color.

(Pardon the tangent; I'm a CPA with computer science experience and so burdened with strange facts.)

In short, these programs need human oversight to be effective tools, which is a trend that financial and tax professionals are already experiencing as they work with vibe-coded tools in their offices. Otherwise, client information could be leaked to the whole internet to see.

Security risks for your retirement tax portfolio

Financial advisors are increasingly using AI to streamline retirement and tax planning. The CFP® Board of Standards has published its own handbook for CFPs to use to "Harnessing AI in the Financial Planning Profession."

Meanwhile, multinational investment firms like BlackRock have built AI into their advisor suites to automate tax-loss harvesting and model retirement outcomes.

AI efficiencies in retirement tax planning can also scan tax returns for overlooked deductions, forecast the top federal tax bracket you'll be in retirement, or even optimize your stock portfolio while you sleep.

Used the wrong way, vibe-coded applications (and AI tools in general) can pose a risk to your retirement savings data:

• Retaining your financial data. If you or your financial advisor uploads your Social Security number, income details, or past tax returns into an LLM, your confidential financial history could become part of the public domain or surface in other users' chats with the AI.
• Compromised retirement accounts. Employees at a financial or advisory firm may use unsecured AI tools on personal laptops rather than vetted, company-approved platforms. This "Shadow AI" lacks proper cybersecurity protocols, potentially leaving sensitive 401(k) and IRA data vulnerable to interception during tax-planning calculations.
• Multi-firm data breaches. AI systems aggregate large data sets on third-party cloud servers to function. If one financial or tax-advisory firm is cyberattacked, the tax data from connected users across all associated firms can be compromised, jeopardizing your data even if the breach didn't occur in your financial advisor's office.
• IRS penalties from AI "hallucinations." AI tools notoriously hallucinate information that sounds legit but is entirely wrong. If blindly followed, this made-up "advice" can lead to noncompliance with federal and state tax agencies, causing you to pay fees, fines, and penalties for faultily reported information (more on that later).

Altogether, unvetted "vibe-coded" apps can lead to significant financial losses for app users, whether you use a financial advisor or not.

Does it get worse? This month, cybersecurity startup RedAccess, which specializes in threat protection against generative AI leaks, reported that 40% of "vibe-coded" web applications identified in their research were actively releasing sensitive information, including financial data, to the World Wide Web.

Platforms like Lovable, Base44, Replit, and Netlify leverage AI to generate functional web applications from simple text prompts — many of these apps are "public-by-default," meaning they were indexed and searchable for the RedAccess team unless a user manually secures them.

RedAccess co-founder and CEO Dor Zvi emphasized the scale of the risk to tech author Andy Greenberg at Wired magazine. "The end result is that organizations are actually leaking private data through vibe-coding applications. This is one of the biggest events ever where people are exposing corporate or other sensitive information to anyone in the world."

Axios reached out to the studied platforms for comment. Lovable spokesperson Samyutha Reddy told Axios that RedAccess did not disclose a list of compromised URLs. Meanwhile, Replit CEO Amjad Masad claimed on X that RedAccess did not share which users were impacted.

How to spot AI-coded apps holding your financial savings

So how do you determine whether your financial savings information is sitting in an unvetted app by your financial planner vs. a "real" application safely vetted by a warm-blooded human being?

Although "vibe coded" isn't a legal term required in your registered financial advisor's paperwork for you to sign, transparency is still mandatory.

Regulators like the Securities and Exchange Commission (SEC) now actively pursue investment advisors for "AI-washing" — or, said another way, overhyping or misrepresenting the use of AI in their financial products.

Yet, depending on how your financial advisor uses AI, a disclosure might not be necessary (though the advisor remains legally liable for AI-washing). If that's the case, here are some "easy tells" to spot a vibe-coded app.

• Hyper-customized. The app does very specific things that generic software can't do (like having niche property management tracking tools).
• The "AI aesthetic." Despite the hyper-specific functionalities, the interface might look as generic as they come (flat layouts, default fonts, gradients, etc.).
• Fast delivery. If you suggest a change and your planner can deliver it the next day, the app may have been vibe coded.

If you have concerns about how AI is used in your relationship with your financial advisor (whether vibe-coded or not), consider asking the following general list of questions:*

1. How is security handled, and where is my data held?
2. Is my data training the AI?
3. How was the app tested?
4. Who owns and maintains the app?
5. Who is responsible for covering losses caused by the AI?
6. How does the AI verify its calculations?
7. What is the human review process?

You should also confirm your advisor's legitimacy by reviewing their Form ADV via the SEC’s website. Additionally, verify specialized certifications — like a CFP® or CFA® — via their respective certifying boards to ensure your advisor meets the highest ethical and educational standards.

If your financial advisor's application (even if vibe-coded) meets regulatory requirements and all other concerns you have, then — great! But if not, you may want to look for a different professional.

*Note: This list is not exhaustive and is compiled from several different sources of industry expert guidance.

Defend against AI-related compliance issues and tax scams

As mentioned, LLMs and AI are known to hallucinate or "make up" information. From a compliance perspective, the IRS doesn't accept "the AI made a mistake" as a legal defense.

So, for example, if the AI you used to prepare your income return "hallucinates" tax write-offs, incorrectly classifies taxable income, or generalizes federal tax laws and ignores your state-specific laws, you will be held liable. This can look like unpaid taxes plus interest and penalties — even if you were simply given "bad tax advice" by the AI.

The Taxpayer Advocate highlighted this when citing a Washington Post review of Intuit TurboTax and H&R Block's AI usage. The review noted that the two companies' chatbots "provided inaccurate or irrelevant responses up to 50 percent of the time when initially asked 16 complex tax questions."

The release went on to state, "Taxpayers are ultimately responsible for the information reported on their tax returns. Therefore, it is essential to review all information carefully, verify calculations, and seek assistance from qualified professionals."

Unfortunately, care with tax preparation doesn't stop during tax season.

AI has also given rise to year-round tax scams, particularly among adults 65 and older, according to the latest McAfee research. This age group reported just a 15% confidence level (out of 100%) in spotting these scams.

• Scammers use AI to clone the voices of family members or trusted tax professionals to demand payment for "clearing up" account issues.
• AI also allows criminals to generate perfectly worded emails that look and sound like the real deal, including IRS correspondence.
• Scammers can also use "vibe coding" to copy an existing, real website to trick you into uploading your information to what appears to be a legitimate website.

Former U.S. Secretary of Defense Robert McNamara once observed that conflict is often a mirror in his 1995 memoir, referring to the Cold War arms race and proxy wars:

This "security dilemma" now defines our AI-led age. As this technology accelerates our financial capabilities, it simultaneously equips bad actors with more sophisticated tools and security vulnerabilities. The result is a perpetual feedback loop where every defensive innovation triggers a more agile criminal counter-strategy.

Yet, focusing solely on the "AI arms race" risks obscuring the genuine utility of vibe-coded tools.

Beyond the scams and security loopholes, vibe coding is already helping several industries perform essential tasks. Some doctors are using platforms like Google AI Studio to "vibe code" personalized applications for patients, while vibe-coded applications can give students customized, interactive study tools.

In the financial realm, vibe coding can also aid your finance pro in tax planning and retirement strategy — if used safely.

The case for AI (and why it isn't all bad)

AI can be incorrect, insecure, and costly. But once you get past those faults, it can be a useful and unique tool. You just need to know what you're signing up for if your financial advisor uses AI.

A human-led, AI-assisted finance expert can utilize this technology to update their retirement tax plan with data-driven insights, like...

• Analyze vast amounts of financial data that would otherwise be unrealistic for a human to pore over.
• Stress-test different market scenarios, helping you to maximize your portfolio's growth.

But finding a reputable financial advisor is a must. Credible professionals translate the AI "legwork" into a tailored plan that aligns with your specific nest egg and lifestyle goals — they don't just do whatever the AI tells them to.

In today's day and age, more than half of Americans may be getting their financial advice from AI, which, for better or for worse, might say something about our society at large.

Regardless of which side of the aisle you stand on — pro-robot, pro-humanity, or a bit of both — stay vigilant and ask questions.

Your retirement tax portfolio may thank you.

....Maybe even literally. I don't know if they send "thank you" cards yet, but it wouldn't surprise me if they did.

Read More

• Don't let a 'mood' trigger a retirement tax trap.
• Here are the ways AI tax scams targeted middle and older adults last year.
• 'Vibes' aren't tax-exempt, but some states won't tax your retirement income.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

The semiconductor industry is booming, defying historical precedents as sales surge amid red-hot demand for costly artificial intelligence chips for data centers. The biggest problem chipmakers have now is that they can’t keep up with demand.

Skyrocketing chip sales push past $1 trillion

Global chip sales will soar past $1.3 trillion in 2026, a whopping 60% rise versus last year, the fastest pace in two decades, according to a recent forecast by Gartner, a tech market research firm. To put the staggering growth in context, back in 2021, industry analysts hoped that yearly sales would hit $1 trillion by 2030.

AI chips will account for 30% of chip sales in 2026. Meanwhile, rising memory demand has caused prices to explode, so memory chips are taking a far bigger cut of total chip revenue. Sales are powered by Big Tech spending that funds massive AI data centers. Alphabet, Amazon, Meta and Microsoft are planning more than $700 billion in capital expenditures this year.

NVIDIA is the biggest winner. Its AI chips used in data centers will see $333 billion in sales in its fiscal 2027 (this calendar year), up over 70% versus the previous year, according to a forecast by Morningstar. It’s the top chip seller, by far. Other chipmakers are riding the wave, including AMD, Samsung, Broadcom, Intel, SK Hynix and Micron. There’s rising demand for alternatives to Nvidia, too, such as chips from Alphabet, Amazon or start-up Cerebras.

AI is shifting what computer chips are needed

A major shift is underway for the chips needed to power soaring AI usage: More central processing units (CPUs) for every graphics processing unit (GPU). GPUs from Nvidia are used to train powerful AI models and also generate text, images, video, data, audio and more.

But CPUs excel at "agentic AI," the autonomous AI tools that take on traditional computing tasks, such as sorting files, querying databases and debugging code. The shift has changed the ratio of CPUs to GPUs needed from 1:8 to 1:4. It’s expected to move to parity or even flip slightly. NVIDIA has a stranglehold on the GPU market, but it also makes CPUs, and recently said it’s on track to make $20 billion in CPU sales this year.

Strengthening CPU demand has Intel’s revenue finally rising, marking the start of a comeback for the long-suffering chipmaker. The company’s bread-and-butter is CPUs and it missed out on the GPU boom needed for building top AI models.

"A year ago, the conversation about Intel was about whether we could survive," said CEO Lip-Bu Tan during Intel’s recent earnings call. "Today is about how quickly we can add manufacturing capacity and scale our supply to meet enormous demand for our products." That includes its flagship Xeon chip line for data centers.

AMD sales are exploding, too, as it looks to outdo Intel in the data center market. "With Intel facing supply issues and unable to meet the insatiable demand for CPUs, AMD benefits as a solid alternative," writes Neil Shah, analyst at Counterpoint research, in a recent article.

"We've seen how AI adoption is really unfolding [and] we're seeing significantly more CPU demand from really every major cloud provider as well as enterprise customers," said CEO Lisa Su in a recent earnings call. Su estimates the CPU market will grow 35% per year over the next five years.

Chip manufacturers race to meet the demand

When it comes to manufacturing leading-edge chips, Taiwan Semiconductor Manufacturing Company (TSMC) still dominates, with huge orders from Nvidia and Apple, plus Broadcom, AMD, Qualcomm and others. Even Intel outsources some advanced chipmaking to TSMC, whose sales will increase 30% this year. TSMC has so much business that some will shift to Samsung and Intel, the only other companies capable of making the most advanced chips.

Intel’s new business of building chips for other chip designers is starting to gain traction, with Apple as a likely new customer. Intel already has deals with Google, Nvidia and others.

Now analysts and investors are watching to see if Intel can get high-volume orders from these tech giants. Intel’s latest leading-edge manufacturing process, known as 18A, is promising, but the real traction happens with the next generation. Known as 14A, the tech is designed for outside customers and is set to go into mass production as early as 2028. Intel hopes 14A offers a direct challenge to TSMC’s tech leadership.

Morningstar forecasts that Intel’s separate business for outside customers, known as Intel Foundry, will make $16 billion by 2030 and $48 billion by 2035. "The Apple deal, if consummated, gives us more confidence in these estimates," writes Morningstar analyst Brian Colello in a recent research note.

A note of caution on chip stocks

When it comes to soaring chip stocks, watch AI spending closely. Many businesses spending money on AI are now scrutinizing the return on investment. Tech giants’ enormous spending assumes that AI demand keeps increasing, as customers find ways to boost productivity, increase sales or streamline operations.

Near term, there’s no sign of AI adoption or spending slowing. AI leader Anthropic, for example, continues to see exploding sales, mostly from businesses. This trend has caused an extraordinary run-up in chip stocks. But if spending starts to cool off and chip sales stumble, investors in chip stocks should look out below.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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From Virginia to California, more than 3,000 data centers are operational across America, with an additional 1,500 coming online. These data centers power the digital lives of people worldwide and make the AI revolution possible. They bring jobs and, in many cases, revitalize communities.

But at what cost to the retirees who live there? Are the improvements worth the side effects?

It's what residents of Box Elder County, Utah, are asking. They are fighting to stop a massive 40,000-acre data center project from going ahead, arguing that it will drain precious water resources, create relentless noise pollution, cause health issues and leave locals with the environmental fallout — all the while, the tech giants receive tax breaks.

They've heard the stories — towns running out of water or electric grids failing — and don't want to see their way of life disrupted as well.

"Data centers are bad for the people in the surrounding areas," says Breena William, a retiree who lives in Box Elder County, where the massive Stratos Data center is being built. "If you look at the experiences of other people, that's my understanding."

This map will tell you if a data center is nearby.

Living near a data center: the common complaints

When it comes to living near a data center, residents, environmentalists, lawmakers and consumer advocates point to several side effects that can negatively impact the quality of life. Some of them include:

Air pollution
Data centers emit hazardous pollutants, such as nitrogen oxides and fine particulate matter, increasing the rate of respiratory diseases and cardiovascular risk. These emissions are from two sources: the data centers themselves and their back-up (often diesel) generators, and the energy required, usually from the electric grid, to power these centers.

U.S. data centers are projected to contribute to nearly 1,300 deaths in 2028, resulting in a health burden of over $20 billion for Americans, according to Cornell University research.

Air pollutants are a concern for residents of Box Elder County. The proposed Stratos facility is expected to hasten the evaporation of the Great Salt Lake. The more of the lake bed that's exposed, the more arsenic and other heavy metals can enter the air.

"I have grandchildren with asthma. I'm really worried about them," says Williams.

Noise pollution
The sound of the generators and the heating and cooling systems creates a constant hum that can be heard hundreds of feet away. Day and night, residents complain of noise pollution that is not only annoying but potentially harmful to hearing.

That was the case for people living next to a data center in Brittany Heights, in Chandler, Arizona. The never-ending high-pitched buzz coming from the data center reportedly rattled windows at night.

It got so bad that residents complained they couldn't sleep and that the noise caused health issues, including vertigo and anxiety. The outcry eventually prompted the city to change its zoning laws to include sound mitigation ordinances.

Water consumption
Data centers need water to keep the computer equipment cool, with a large data center using as much as 5 million gallons of water a day. They tap local resources for that water, draining what is left for residents. It can become a problem when the data center is located in a region with limited water.

Residents of The Dalles, Oregon, learned that the hard way. Thanks to its energy infrastructure, water availability and vast land available for development, the community had become a favorite of many major tech companies looking to set down roots for data centers.

But when Google wanted to expand and wouldn't disclose how much water it consumes, it sparked a 13-month legal battle. When Google's water consumption was finally released, it showed the data center used more than a quarter of the city's water supply.

Higher utility prices
Data centers need a massive amount of electricity, but critics contend they don't pay full price for that. The burden is passed on to residential customers, who must pay more as a result.

A study by Carnegie Mellon University projected that, by 2030, the growth of data centers will drive regional demand by 20% to 30% annually. That will increase electricity bills by an estimated 8% nationally and up to 25% in some regions.

"These large data centers use so much energy, put so much pressure on the local utility systems, they have to invest in a ton of infrastructure upgrades," says Jenn Jones, vice president of financial security and livable communities at AARP. AARP is backing legislation that protects consumers when data centers come to their neighborhoods. "We don't think those costs should be borne by consumers, especially older adults living on a fixed income."

Older adults seem to agree. A national AARP survey found 78% of adults age 50+ believe large data centers should pay their own way, and 75% agree that state policymakers should act to protect consumers from rising utility costs tied to data centers.

Property value pressures

The jury is still out as to the impact living near a data center has on the sale of your home. In some areas, it can boost property values; in others depress them.

A 2025 George Mason study of Virginia, a state with a high concentration of data centers, found that they increased property values.

The reason: data centers tend to be located in areas that already have good roads, reliable utilities and are close to airports. Attributes that homebuyers also want.

But that isn't putting residents at ease. William of Box Elder County is worried that Stratos could make the land near it uninhabitable, which would drive the property values down.

"I think after this goes into effect, people won't be able to sell their homes, and people will be stuck," says William, who is worried enough to consider putting her house up for sale. "Something away from a data center, if we can find it."

Source: DataCenterMap

Can the benefits really be overlooked?

There are reasons to be concerned about the impact of data centers. But can some benefits be overlooked? After all, these data centers do pay taxes, bring jobs and build an infrastructure to support them. That can revitalize a community that would otherwise struggle. Tax revenue can fund community upgrades, pay for schools and provide services that retirees rely on.

According to the Data Center Coalition, an industry trade group, in 2025 the U.S. data center industry supported 5.5 million jobs, contributed $927 billion to the U.S. GDP and generated $204 billion in federal, state and local taxes.

"The trade-off of having data centers is they bring jobs, tax revenue, infrastructure and economic development," says Sanjay Patnaik, a senior fellow and director of the Center on Regulation and Markets at Brookings. "You need some economic activity in a county, otherwise you don't have tax revenue."

There's also the potential national security risk that Shark Tank's Kevin O'Leary — one of the investors behind the Stratos data center in Box Elder County, Utah — points to. He reportedly says the U.S. needs more data centers like Stratos to stay ahead of China in the AI "arms race."

Time will tell

Data centers will continue to pop up, and residents will lose some battles and win others in their fights to stop them.

But whether you support one coming to your retirement community boils down to a cost-benefit analysis. Are the economic benefits more important than the environmental and health risks?

"I would advise people to look at what the alternative is," says Patnaik. "Do they want to have a data center in their backyard and get some economic growth, or do they want nothing in their backyard?"

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SpaceX's S-1 filing is finally public, and for investors, the biggest mistake would be looking at this company as a rocket launcher.

That is not what SpaceX is anymore.

This is now a vertically integrated infrastructure company sitting at the center of space transportation, global communications, defense, artificial intelligence, compute, data transport and, potentially, chip manufacturing.

That is why the S-1 filing matters so much. It gives public market investors their first real look at a company that has been private for more than two decades and is now preparing for what could be the largest IPO in history.

The first thing I would tell investors is this: Do not get distracted by the headline valuation alone (about $1.75 trillion to $2 trillion, according to Reuters).

The real question is whether SpaceX is building the infrastructure layer for the next generation of the economy. In my opinion, that is the only way to evaluate this company.

Starlink is still the primary revenue driver

A lot of investors still think of SpaceX through the lens of launches. Falcon 9, Falcon Heavy and Starship get most of the attention because rockets are exciting. But from an investor perspective, Starlink remains one of the most important parts of the story.

The filing shows why. Starlink is not just a satellite internet product. It is global connectivity infrastructure. Residential broadband is one piece of it, but the bigger opportunity is much broader: Enterprise connectivity, government contracts, military communications through Starshield and, eventually, direct-to-cell service.

That last piece is important. SpaceX's spectrum strategy and direct-to-cell opportunity could eventually put the company in competition with wireless carriers such as AT&T, Verizon and T-Mobile.

It is still early, and investors should not assume that will happen overnight. But the direction is clear. SpaceX is not only trying to connect homes. It is trying to own the infrastructure that connects people, devices, governments and machines anywhere on Earth.

For ultra-high-net-worth investors, that is the point. The opportunity is not simply broadband revenue. The opportunity is platform control.

Governance will be a real concern for institutions

The filing also raises a governance issue that institutional investors will have to wrestle with. SpaceX is using a dual-class share structure, with Class A shares carrying one vote and Class B shares carrying 10 votes. Elon Musk is expected to retain voting control.

For many institutional investors, that is a red flag. They generally do not like one person having that much control over a public company.

I understand that concern. But I also think SpaceX is an unusual case. In a normal public company, this level of control might be a deal breaker. With SpaceX, the market may decide that access matters more than governance.

That does not mean investors should ignore the risk. They should price it in. Musk's control means investors are not just underwriting the business. They are underwriting his leadership, decision-making and long-term vision.

Personally, I prefer that he maintain control, because this is not a company that can be managed quarter to quarter. SpaceX is attempting projects that require long time horizons, massive capital investment and an unusually high tolerance for failure.

Old-school governance may not fit a company trying to build reusable rockets, orbital data centers and a Mars transportation system at the same time.

The xAI burn is big, but look at the compute revenue

The most obvious financial concern is capital intensity, especially around xAI. The filing shows just how expensive the AI side of the business is. The capital expenditures by xAI are massive, essentially running at a scale that looks like roughly a billion dollars a month.

That will scare some investors. I get it.

But the mistake would be looking only at the burn rate and ignoring the revenue opportunity that compute creates. The Anthropic compute agreement is one of the most important pieces of the filing. SpaceX is effectively monetizing Colossus compute capacity, and that deal generates roughly $1.25 billion per month through 2029.

That changes how investors should look at xAI. Yes, it is capital-intensive. But if the company can turn compute into recurring revenue, the story looks very different.

AI infrastructure is expensive for everyone. The question is who can lower the cost curve over time and control enough infrastructure to turn that spend into a durable business.

That is where SpaceX has a potential advantage.

Starship is the execution risk investors cannot ignore

Starship is crucial to the long-term thesis. If Falcon 9 made space more reusable, Starship could make space scalable.

That matters because almost every major future opportunity depends on lowering launch costs.

• More Starlink satellites
• Larger payloads
• Orbital data centers
• Moon infrastructure
• Mars
• Defense systems
• AI compute in space

Right now, the economics of space-based infrastructure depend heavily on the cost per kilogram to orbit. If SpaceX can bring that cost down meaningfully, the entire business model changes. If it cannot, many of the most ambitious opportunities remain theoretical.

That is why Starship execution is one of the biggest risks in the IPO filing. Investors should watch test flights, FAA approvals, launch cadence and reusability progress closely. A successful Starship program could accelerate nearly every segment of SpaceX. Delays or failures could slow the entire thesis.

The AI story is bigger than Grok

Retail investors may focus on Grok because it is the most visible part of xAI. I do not think that is the right way to look at it.

The bigger AI story is infrastructure: Compute, coding, data centers, chips and distribution. The potential Cursor deal matters because coding is one of the areas where xAI needs to compete more aggressively with Anthropic and OpenAI.

Terafab also matters because chip manufacturing and compute supply are becoming strategic necessities.

The companies that win AI will not just have the best chatbot. They will control the infrastructure that makes AI cheaper, faster and more scalable.

That is why orbital data centers are so important. They are still unproven at scale, and investors should treat them as a high-risk, high-upside part of the thesis. But if SpaceX can make space-based compute cheaper than Earth-based compute, it could change the economics of AI infrastructure entirely.

Unlimited solar power, fewer cooling constraints and no "not in my backyard" data center politics could become a serious advantage. The key word is "could." It still has to be proven.

The infrastructure thesis investors should understand

SpaceX is not being valued as a rocket company because it is no longer just a rocket company.

The filing makes that very clear. This is now a communications, transportation, AI and infrastructure company all under one roof.

Yes, there are risks.

• Starship still needs to execute
• AI remains extremely capital-intensive
• Regulatory approvals will matter
• Some institutional investors will likely remain uncomfortable with Musk's level of control

But in my opinion, many investors still are not fully understanding where this company is going. If SpaceX succeeds in scaling Starlink, lowering launch costs and building orbital infrastructure for AI and global connectivity, it becomes very difficult to see who can realistically compete with it.

That is why I believe the market will eventually look back at this IPO as far more than just another technology listing. It could end up being the moment investors realized SpaceX was building the infrastructure backbone for the next generation of the global economy.

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• Hot Upcoming IPOs to Watch

This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Trust is in short supply these days, and not just in Washington.

Across American workplaces, confidence in leadership, information and intent has eroded, according to Gallup, in subtle yet deeply consequential ways. The result isn't just cultural discomfort; it's a direct hit to productivity, collaboration and performance.

Politics will grapple with the trust deficit in its own fashion. In business, however, the responsibility is more immediate and more actionable. Rebuilding trust isn't a messaging exercise: It requires a fundamental shift in how leaders show up, communicate and make decisions.

Why now? The ground has shifted. Employees operate in a more complex, skeptical information environment. The line between fact and fiction feels more blurred than ever.

Conflicting narratives and AI-driven deepfakes amplify this confusion. In this environment, trust is no longer assumed. It has to be earned — deliberately and consistently.

Adapting to an AI-integrated workplace hinges on one thing: Trust. Not the kind you frame on a wall, but trust that is built into the operational fabric of the organization. It shows up in how communication flows, decisions are made and how organizations learn at scale.

This is especially true now. People curate their own information streams and shape their own versions of reality, typically validating their existing world view. Inside and outside the workplace, individuals gravitate toward like-minded perspectives. Cliques reinforce these viewpoints.

Breaking through these filters requires leaders to be deliberate, consistent and credible, which requires them to go beyond traditional culture efforts.

The bottom line: Barriers are going up inside your organization. It's up to capable, forward-thinking leaders to break through them, earn buy-in, build confidence and make a clear, credible case for the path forward.

Fear of losing control

According to the 2026 Edelman Trust Barometer, a global survey of more than 33,000 people across 28 countries, 70% of people are now unwilling or hesitant to trust someone who differs from them in values, background, culture or approach to social issues.

This isn't polarization anymore. It's something more insidious: Insularity. And it's quietly destroying collaboration, productivity and innovation in workplaces everywhere.

The consequences are stark and measurable. Forty-two percent say they would rather switch departments than report to a manager with different values. Thirty-four percent say they would put less effort into helping a project team leader who has different political beliefs.

This isn't about office politics or personality conflicts. This is a fundamental breakdown of the social contract that underpins organizations' functioning.

When teams can't trust across differences, projects stall. Innovation dies. The best ideation is disrupted due to the lack of cognitive diversity and constructive conflict.

The result: People self-segregate into their ideological comfort zone.

Even within this environment, there's a clear path forward if leaders address the underlying dynamics head-on. Start with a simple reality: A meaningful segment of your workforce will be hesitant to embrace any change and specifically AI-driven change designed to boost productivity gains.

Why? It's not fear of change. It's fear of losing control.

AI, by its nature, makes people feel displaced in their own roles. According to a 2026 ADP research survey, only 22% felt their job was safe from elimination, with workers reporting feeling less certain about where they fit, how decisions are made and what remains in their hands.

That perceived loss of control fuels anxiety. The issue isn't the technology itself; it's the uncertainty it creates. When people feel they no longer have agency, resistance follows. Understanding that distinction is the first step to address it.

Leaders must recognize this fundamental shift in the workplace. Focus on empowering your people to expand their capacity to process everything happening. The only way to expand it is by raising their level of awareness.

The co-creation principle

There is a practical way through this: Involve people in building what comes next because people commit to what they help create.

As AI integration reshapes workflows, decision-making and expectations, employees' voices should be integrated into the design process. Let them help choose what tools are used, how processes evolve and what new norms take hold. Participation drives ownership, and ownership drives adoption.

That's why the age of AI isn't just a technology shift — it's a cultural one. And culture still does what it has always done: It determines whether strategy actually works. You can have the best AI roadmap in the world, but if the culture resists it, progress stalls.

In the past, organizations could operate with a baseline level of skepticism and still function. In an AI-driven workplace, that's no longer the case. Without trust, adoption slows, collaboration weakens and productivity suffers. Building that trust isn't optional. It's fundamental.

For organizations, the path forward requires discipline. Recognizing the environment you are actually operating in, not the one you wish existed. Then, take a hard look inward. Where are you misaligned between intention and execution, strategy and rewards, culture and compensation?

From there, move into action. Build human verification into AI workflows. Train your systems properly, because the old rule still applies: Garbage in, garbage out.

Just as important: Design environments that help people stay grounded and focused. Invest in practices that build resilience and expand capacity across the organization.

And through it all, engage your employees in the process. Give them a voice in shaping change.

I said it before and I will say it again, people commit to what they help create. In a low-trust, AI-driven workplace, that may be the most important advantage you have.

So take the lead: Invite your team to co-create. Organizations that figure this out won't just survive the age of insularity; they'll define what workplace success looks like on the other side.

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• Looking to Adopt AI in Your Finance Org? Consider These Factors First

This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

Businesses need to prepare for state privacy law enforcement, and fast. Total privacy fines in all 50 states soared to $3.4 billion in 2025, versus $1.8 billion in 2024, according to a recent analysis by Gartner, a tech market research firm.

For perspective, the total was just $1.2 million in 2023, before a frenzy of new state enforcement action took off. Penalties hit companies of all sizes and across industries: Health care, finance, software, communications, insurance, entertainment, retail, tech, legal, advertising and more.

The payouts stem from both state fines and lawsuits brought under these laws by injured parties. The state laws enshrine consumer rights and data protections that companies must abide by. Gartner says 22 states have passed privacy legislation aimed at consumer rights and another 24 are expected to pass privacy legislation in the coming five years.

State regulations related to the use of AI are expanding fast, too. More than 100 state laws covering artificial intelligence were passed last year, while state agencies also issued new AI-related guidance. For example, in California, the leader in privacy enforcement, a rule covers automated decision-making in job recruitment and employment.

"A lot of organizations have let their privacy policies atrophy," says Nader Henein, an analyst at Gartner who compiled the data. Many privacy programs were implemented years ago when California passed its sweeping privacy law in 2018, which was enacted in 2020. The landmark law provides consumers the right to know about the personal information being collected from them and how it’s used; the right to delete personal info collected by the company; and the right to opt out of the sale or sharing of personal info.

Notable Enforcements by the California Privacy Protection Agency in 2025

• $1.35 million fine against Tractor Supply
• $345,178 fine against Todd Snyder Inc., a clothing retailer
• $632,500 fine against American Honda Motor Co.
• Forced the shutdown of Background Alert, a data broker

"Companies should dust off their privacy program and assess whether it works," says Henein. They should check to make sure those policies are being implemented and cover new rules being rolled out. Gartner also recommends focusing on the online user experience, since most of the violations come from the privacy user interface, such as website privacy notices.

Companies doing business in multiple states should default to the one with the most onerous rules. For example, if consumers have a right to their personal data within 45 days of requesting it in one state, and 30 days in another, the target should be 30 days across the board, says Henein. In practice, that could mean a 20-day policy to ensure compliance.

"Most business-to-consumer companies have bought privacy software," says Henein. Vendors include OneTrust, TrustArc, Osano or TrueVault, and the software often includes AI-related governance. Nader says business-to-business companies, and smaller companies that cater to consumers, may use a more piecemeal approach.

These mounting compliance costs are sure to catch the attention of Congress. But a federal law that preempts the states is unlikely anytime soon, leaving businesses to cope with a patchwork of state laws.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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It's hard to avoid stories about AI in the news or on social media these days. The technology is widely expected to be transformative, although the extent and the speed at which it will impact society is not well understood.

Anthropic, the maker of AI model Claude, has been in the news lately for several different reasons. In late March, the company admitted it had accidentally posted some of Claude's source code online.

While this didn't expose any user data or confidential information directly, there is some concern that bad actors could use this information to build rogue agents or find ways to inject malicious commands into the tool's workflows.

Meanwhile, it has also introduced its next big model: Mythos (paywall). This AI model is said to have the ability to find thousands of vulnerabilities in corporate software, and is likely to be able to find unknown vulnerabilities autonomously.

Jamie Dimon, CEO of JPMorgan Chase, mentioned Mythos on a recent earnings call, suggesting our entire financial system could now be at risk from cybersecurity threats because it is so interconnected. Exposing potential failure points impacts the whole system.

In general, as AI companies like Anthropic, OpenAI, Meta and others all race to release new tools with the best features, attention to security seems to be falling by the wayside as speed is prioritized.

As an individual and an investor, how do you help protect yourself given the vulnerabilities, both known and unknown, that AI is exposing?

Control what you store in AI's memory — and what you connect it to

For starters, be prudent with the personal information you share with AI tools, such as ChatGPT, Claude, Gemini and Perplexity. These tools typically store your data by default unless you tell them not to.

They do this to enhance the user experience and make your chat results more customized over time. They might even seem to read your mind when you ask questions in the future.

However, this does mean they may be storing your preferences or information you share, such as your occupation, personal information gleaned from your questions and any documents and images you upload.

If you share medical records or questions, they may also store highly confidential facts about your health history.

When you also consider that bad actors on the internet are looking for ways to trick AI tools into sharing user data — a technique called "prompt injection" — it seems sensible to limit the sensitive information you hand over.

When setting up an account with an AI tool, consider strongly whether or not to disable the memory functions. Doing so in just a few clicks could help reduce the chance that a potential future data breach would expose personal data you don't want disseminated.

Keep your devices up to date

We may soon be seeing a flurry of critical software updates from big tech companies, such as Microsoft, Google and Apple, as they use pilot access to Mythos to identify and remediate vulnerabilities not previously detected.

Keeping your devices up to date will be crucial. Other AI models currently in development, not just Mythos, will likely make this our new reality. People holding on to old computers or smartphones no longer receiving software updates may be putting themselves at a higher risk of being accessed by bad guys.

Keep your data private

Social media apps leave all privacy protections turned off by design, unless you proactively enable them. That means apps like Facebook and Instagram collect as much information as possible regarding your tastes and preferences, and services like Google will store your browsing history and location data if you use features like Google Maps.

If any of these services are hacked, your personal data could potentially be at risk.

As AI agents can now connect to other services to automate work for you, there is always the possibility that personal data stored in an app you use could be shared with other systems.

For example, Claude can now connect to Gmail and Google Drive (when you choose to give it access), giving it the ability to search through your emails and files. That could be a great productivity enhancement for some of us, but it is important to think through the privacy implications.

Similarly, automation tools like Microsoft Copilot Tasks allow an AI agent to perform repetitive tasks in a browser for you, but it may require access to specific website usernames and passwords and store those to perform routines on a schedule.

Limit public information about you on the internet

Data breaches are still a major risk to individuals and could become more common if models like Mythos fall into the wrong hands. To guard against that, consider limiting how many websites you have accounts with and how many sites contain your personal data.

You can also ask data broker sites to delete your personal information or pay services such as Incogni or Optery to do it for you. This doesn't ensure 100% deletion of your data from the internet, but it does reduce its footprint.

Part of this effort should also include limiting the number of websites you create accounts with and give your phone number, address or credit card details to. When you sign up for rewards programs or shopping accounts, it all adds incrementally to your digital footprint.

As the possibility of breaches due to new vulnerabilities increases, any site that contains personally identifiable information for you could be used in future phishing or impersonation attacks.

Also, remember that AI training model data may include information publicly available on the internet, so it may also scrape any information posted about you online.

Choose the financial institutions you work with

Thinking about how this could impact you financially, the risk is that increasingly sophisticated AI models could potentially be used to hack banks, exchanges or brokerages, putting your money and financial information at risk.

Individual investors may not be able to do much about this on their own, apart from choosing to work with larger financial institutions with stronger cyber protections and larger IT departments actively engaged in preventing intrusions.

Smaller financial institutions will need to be adept at managing their technology and patching any gaps in their security.

Perhaps over time, AI could be used to improve cyber defenses, but in the short run, new AI model functions may be tilting the balance in favor of bad actors. The prospect of having an adversary probing and testing for vulnerabilities in the software and systems of banks and exchanges will be daunting for security professionals.

Institutions may need to dedicate more money and resources to protecting their environment as technologies evolve.

We will all need to continue to be diligent with our security by moderating what data we share with AI tools so we can leverage their abilities.

The old adage "trust but verify" seems relevant here. Make sure your online accounts are not sharing your personal details by default, and be skeptical when allowing AI tools to connect to your email and data storage accounts.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

If cutting-edge artificial intelligence could truly tame the daily onslaught of emails, it would make a huge difference for tens of millions of workers. Microsoft, which dominates workplace email with Outlook, thinks it has a solution with its AI-assistant, Copilot.

"Until now, Copilot in Outlook helped with the task in front of you: drafting an email, catching up on a long thread, or finding a time to meet," Microsoft says in a recent blog post. "Copilot in Outlook is now agentic, taking on the ongoing work of running your inbox and calendar."

That tech update, if it works well, means that a helpful tool is turning into a true personal assistant, with the ability to tackle complicated inbox tasks. Microsoft says its AI tool can automatically schedule meetings, send emails to coworkers and recommend which meetings to decline. It promises to automate follow-ups with employees that haven’t responded, pinpoint messages that are urgent and reschedule conflicts.

To make the system work, users write simple commands for the Copilot chatbot. For keeping tabs on responses to an important project, Microsoft says to tell the Copilot chatbot to "Identify people who haven’t replied to my emails after 24 hours, prioritize the ones that matter most, and draft polite follow-up emails for me."

For complex emails, the company suggests writing, "Pull the latest updates on [project name] over the last week. Draft a confidential, high‑importance update email for my manager." After a week off, try telling Copilot, "I just returned from vacation. Help me catch up: summarize what I’ve missed, highlight what’s most urgent, and draft a short briefing email. Then suggest emails I can safely archive and 1-2 tasks I should focus on first."

This type of automation holds promise but could also create new problems. If workers are increasingly responding back and forth to AI-created messages rather than human-written ones, there could be more confusion and miscommunication. The accuracy of automated decision-making and AI’s ability to understand nuance are other key elements that will make or break the tech.

As these capabilities roll out to tens of millions of workers, it could mark a major shift in workplace communication. The potential for time savings is very real, especially for managers, salespeople and other workers inundated with messages that require a response.

The AI-enhanced features are currently available for those in a Microsoft AI early adopter program and require a Copilot subscription, which ranges from about $20-$30 per user per month. Expect it to be widely available soon for Copilot subscribers.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Controversy swirls over whether AI is a bubble — and whether the excitement about its potential is overblown and will one day peter out.

But many people don't know that they are already using AI — and they're using it quite a bit. If more people knew what AI does, how it does it and what changes it has brought, they wouldn't believe it's a boom/bust industry.

According to a recent study by Gallup Newsletters and Telescope, 99% of Americans have used a product that uses AI as part of its operation, but only 64% of those people realized that AI was involved.

Stanford University's HAI Institute, in its latest Index Report, states, "AI is poised to be the most transformative technology of the 21st century."

The Index Report points out that AI is growing rapidly, and in the year 2023, the number of AI-enabled medical devices approved by the FDA was 223. This was up from only six approved in 2015.

Another rapidly growing AI technology: Self-driving cars, which offer service to a large and rapidly growing customer base. As of 2024, Waymo reported it was operating more than 150,000 weekly autonomous rides.

Private U.S. AI investment has also grown, hitting $109.1 billion in 2024 — far more than any other country. The next-highest country was China, at $9.3 billion.

What the experts say

Tech executives and experts expect AI to continue flourishing. In a recent Nvidia blog post, it was noted that, during the keynote address at a company event, CEO Jensen Huang highlighted the rise of AI companies such as OpenAI and Anthropic. "This last year, it just skyrocketed," Huang said, pointing to the $150 billion that was invested in venture startups.

He added that demand for Nvidia GPUs (graphics processing units) is "off the charts" and that he believes "computing demand has increased by one million times over the last few years."

Tim Bajarin, a prominent tech consultant and a principal at market research firm Creative Strategies, also doesn't think AI is a bubble. He told me in an interview that he thinks now is a good time for AI. "We only know about an eighth of what it can do," he said.

"Many companies are (already) using intelligence to answer questions from their customers," he pointed out, "like, 'Where's my order?' or 'When will it be shipped?'" A search engine, he said, can answer questions like that quickly and cost effectively.

While acknowledging that many people worry that AI will increase unemployment, Bajarin notes that AI could also create jobs. "Some jobs can be automated. We're already seeing that. Salesforce laid off 4,000 customer service people because talent was not being used."

He recommends that workers learn to use AI tools and strive to be part of AI's development.

AI is a developing tool

All that said, AI's future results might end up being in the middle of present expectations — not as miraculous as some think, nor as bogus as others believe.

We know that AI is helpful for personal use and is used in important industries like healthcare, transportation, entertainment and finance.

Companies are investing real dollars in AI, making its growth more certain. Investors could consider investing in the sector. Many tech companies are tied to AI, and their stocks could trade with the sector's growth.

Some investment choices to consider

Nvidia (NVDA) continues to look interesting, even after climbing over 1,300% in the past five years. Morningstar shows good earnings growth, and with its current PEG ratio of 0.50 on March 15, its market price is quite reasonable.

A package approach could be a good choice for investors wanting to spread the risk, and some small-cap stocks offer value. Using the iShares Russell 2000 ETF (IWM) as an example, small-cap stocks have been outperforming the S&P 500 year to date as of March 15, 2026.

The Invesco S&P SmallCap Information Technology ETF (PSCT) includes stocks of companies that supply information technology products and services. Over the past year, as well as year to date, PSCT has outperformed the S&P 500 index, as of March 15, 2026.

Morningstar shows PSCT with a PEG ratio of 1.20 based on future earnings. This is a reasonable ratio. PSCT showed a loss of $1.29 per share in past earnings.

Another interesting ETF is the Roundhill Generative AI & Technology ETF (CHAT). CHAT holds the stocks of global companies, including emerging markets, that are involved in AI. The ETF is invested in large-caps, and its largest holdings include Alphabet (GOOGL), Nvidia, Samsung Electronics, Microsoft (MSFT) and SK Hynix, an emerging markets technology company. (Note: My clients hold NVDA, and I hold CHAT.)

CHAT has outperformed the S&P 500 index in both the past six months and the past five years, as of March 19, 2026. It also seems reasonably valued. Morningstar's PEG ratio is 1.04. Note that Morningstar estimates that future long-term earnings could be down about 30% from past historical earnings. Based on the lower estimates, however, the PEG ratio would be a reasonable 0.71.

Where we are

So, where does this leave us on the "AI bubble" question? The controversy over whether a bubble exists seems to miss the fact that most of us are already using AI daily, often without realizing it.

We're at only the beginning of learning AI's potential, and we're seeing massive investment and rapid growth across major industries like healthcare, transportation and finance. So while the future may not be as miraculous as some predict, nor as bogus as others fear, the data confirms that companies are investing real dollars, making AI's continued growth more certain.

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• Should You Invest in the Quantum Computing Sector?

This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

The gap between firms that have built AI workflows and those still running on legacy tools is widening.

Firms with integrated AI are doing more client work with the same staff. If you are still evaluating, you are not holding your position. You are losing ground.

Google's AI ecosystem is worth a close look because it runs on infrastructure your firm most likely already has. If you use Workspace, you already have the foundation.

The suite adds Gemini, NotebookLM, Nano Banana Pro, Veo 3, Flow, Google Vids and Whisk on top of what you already pay for. Apply any of them with structure and the returns are immediate.

Each section below covers what the tool does and where it fits in a real advisory workflow.

1. Gemini: The core engine behind Google's ecosystem

Gemini is the model powering most of Google's AI strategy. It handles text, images, voice and code, and it reasons across all of them. Google embedded it directly in Workspace, so your team can access it without leaving Gmail, Docs, Sheets, Slides or Meet.

Where it fits: Gemini handles drafting work your team already does manually: Market commentary, client letters, meeting summaries and internal memos. It also summarizes long email threads and cuts the time your team spends on administrative preparation.

The bottom line: Gemini is not a standalone product. It is an engine that strengthens the workflows your team already runs in Workspace. If you run on Google, you have it today.

2. NotebookLM: A research assistant for content-heavy firms

NotebookLM lets you upload source documents and query them conversationally. Load it with regulatory updates, investment research, compliance memos or training materials and it processes everything, so your team can ask questions and get structured answers without reading through every page.

Where it fits: Your analysts can get a summary of a 40-page regulatory update without reading it in full. Your advisors can pull client-ready talking points from research reports they do not have time to process. Your compliance team can cross-reference documents without handling each one individually.

The bottom line: NotebookLM removes the single most consistent drag on advisory productivity: The time it takes to read and synthesize large amounts of written material. If your team is buried in documents, start here.

3. Nano Banana Pro: Google's image generation and editing system

Nano Banana Pro is Google's image generation and editing model, built on Gemini 3 Pro and released in November 2025. It creates branded visuals and infographics at up to 4K resolution, with precise control over lighting, color and layout. It also renders accurate text in multiple languages directly in the image.

Where it fits: Your marketing team can produce graphics for newsletters, webinars and adviser presentations without waiting on a designer. Your advisers can build visual aids that help explain financial concepts to clients without needing a creative team behind them. If you serve international clients, the multilingual text rendering adds practical range.

The bottom line: Nano Banana Pro cuts your design cycle and your cost per piece. You spend less time waiting on outside creative resources.

4. Veo 3: Cinematic video generation for professional storytelling

Veo 3 is Google's video generation model. Feed it a script, a prompt or reference images and it produces cinematic-quality video with realistic camera motion, lighting and scene composition. The output quality is approaching commercial production standards.

Where it fits: You can use Veo 3 for quarterly market updates, conference openers and adviser-produced client communications. Your investment team can convert a complex research thesis into a two-minute video a client will actually watch, without a production crew. Your advisers can record personalized welcome videos on their own.

The bottom line: Veo 3 is for firms that want to compete on content quality without the cost of an in-house studio. The production barrier drops. The brand quality does not have to.

5. Flow: The editing and production system built for scale

Flow is Google's video editing and production platform. It does not generate video. It takes what you already have, assembles it into branded scenes, and outputs a finished cut ready for distribution.

Where it fits: Your marketing team can cut a long webinar into usable short clips in an afternoon. Your branch offices can produce adviser content to a consistent standard without rebuilding the process each time. Your operations team can turn a new policy into a training video the same day it is written.

The bottom line: Flow enforces consistency at scale. The quality of the output does not depend on who built it.

6. Google Vids: Fast script-to-video creation

Google Vids converts a script into a short video using stock footage and basic narration. It is the lightest tool in the suite and the one with the lowest barrier to entry.

Where it fits: Use it to build onboarding content and adviser training modules. It is also the right tool for policy updates and social posts where the message needs to be short and the production needs to be fast.

The bottom line: Google Vids is where to start if your team has never produced video. The learning curve is flat.

7. Whisk: A creative ideation tool for campaigns and branding

Whisk helps your team explore visual directions and campaign concepts before committing to production. It generates mood boards, color palettes and layout concepts so your team can align on creative direction before anyone spends real budget.

Where it fits: Your marketing team can use it to pressure-test visual concepts for a campaign or rebrand before spending anything on execution. It is cheap to explore and expensive to redo.

The bottom line: Whisk is a planning tool. Settle your creative direction here before you commit production budget to Veo 3 or Flow.

8. Workspace AI: The quiet productivity driver

The AI features built directly into Workspace often deliver the fastest return because they require the least disruption.

Your team can summarize meetings and write first drafts with fewer manual steps. Sheets and Slides get the same treatment. No new software. No change management program.

The bottom line: Workspace AI is where most firms should start. The lift is immediate and the barrier to entry is near zero.

Strategic recommendations for firm leaders

Getting value from these tools requires more than access. Before you deploy broadly, do these five things.

1. Start with NotebookLM or Workspace AI. Neither requires new infrastructure or a rollout plan. Both connect to content your team already produces. You will see measurable time savings within the first month. Prove the value before you expand.

2. Lock down your data controls before anything goes live. Confirm that client and firm data will not feed model training. Review your data processing agreements with Google. This is a compliance prerequisite, not a configuration detail.

3. Put a review process in writing for client-facing content. A review by an adviser, compliance or marketing is needed before anything reaches a client. Document who reviews what, and when, before the first AI-assisted piece leaves your firm.

4. Build prompt templates and a short style guide before you deploy broadly. Consistent outputs require consistent inputs. One day of preparation prevents weeks of inconsistent output.

5. Measure outcomes from day one. Track turnaround time, content volume and team member satisfaction. The data you build now is what justifies the next phase of investment.

Conclusion

Google's AI ecosystem gives your firm a direct path to better client communication at lower operating cost. These tools do not replace your advisers or your compliance process. They give your team more capacity to do the work that builds client relationships.

Your competitors are not waiting. The firms building structured AI workflows today are gaining a cost and capacity advantage that compounds every quarter. The ones that hold off will keep subsidizing the gap with margin, and eventually with clients.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Just about every day now, I get emails and phone calls from readers asking the same question: "With what we are seeing, AI is leading to the wholesale firing of hundreds of thousands of employees across entire industries. Should I consider law as a career?"

My answer: Let history be your guide. Consider these questions:

• What was the dominant means of transportation in the early 1900s in villages and cities across our country?
• Who, and in which profession, assured their dependability?
• How many of them were there in the late 19^th century? How many now?
• What one factor explained their vanishing as a primary industry, and when it first emerged, was it seen as a threat to their profession?

Indispensable to daily life

The answer: The village smithy, aka the blacksmith, assured that horses could provide the transportation that was indispensable to daily life. Blacksmiths numbered in the hundreds of thousands in the late 19^th century, but there are only about 10,000 today.

When the first automobiles hit the market, they were seen as playthings of the wealthy, not a threat to the respected role blacksmiths held in society.

I submit that AI is today's equivalent of the automobile, and it's having a similar impact on the legal profession as law firms no longer require dozens of junior lawyers to search through millions of pages to find a smoking gun when AI can do it, and so much more, in minutes.

Solving a problem without a lawyer

One of my clients, "Dr. Dan," called the other day, thrilled to tell me how he'd used AI to avoid becoming the victim of his landlord's unreasonable requests. "She sent a modification to our lease that made no sense at all. I could have called you, but first I asked AI if this was legal and reasonable and how could I politely reply.

"AI said that it was not legal and asked if I wanted a response that I could send, in lawyerlike language, explaining why the landlord was wrong. I typed, 'yes,' and in a couple of seconds, I got a beautifully reasoned response, which I sent to her.

"She phoned me right back saying, 'Dan, you're right. But tell me, how much did your lawyer charge you for this letter? It is so well written!' We had a good laugh. I think AI is going to put a lot of lawyers out of work."

What do law school deans and admissions officers say?

To get a feel for what the top brass in higher education have to say, I reached out to several deans and admissions officers and left this voicemail: "How will AI impact law? Today, would you advise a family member to apply to law school? Also, can you explain the enormous increase in applications to law schools the past several decades?"

Two agreed to discuss these issues on condition of anonymity so they could be perfectly candid, and both noted one of the most important reasons we have seen an enormous increase in the number of law students over the past few decades: Money (for the schools).

"The growth in law school enrollment hasn't matched the actual need for new lawyers," said the dean at a Midwest law school. I'll call her Anna. "The ratio of lawyers to the U.S. population today is four times what it was in 1970, and many of our graduates are underemployed and facing enormous student loan debt.

"The explosive growth in admissions over the last 50 years was primarily because law school is a cash cow for universities.

"We can't lose — but no one cared if students would get hired into positions where they could have a decent life and repay their loans.

"And the more students we admit, the greater the damage will be due to AI. Law schools are motivated by tuition, not placement. It is as if we are graduating manual laborers into a robot-factory economy, and there will be pain."

Big, bad gamble

The dean of a Southern law school, whom I'll call Stacey, pointed out, "As we speak, law school enrollment is surging, and many students are making a horribly bad bet on future, high-income employment. The supply-and-demand mismatch will be horrible as AI adoption scales upward."

Both educators provided this gloomy outlook on the future: Law school graduates of 2027 and 2028 will be entering a job market where AI has progressed from the testing stage to real, daily operational functionality.

Their advice: Look for a law school with a curriculum that teaches how to use AI — those courses will impress an employer.

So, here is what anyone considering law school needs to keep in mind: Just as the Model T didn't put blacksmiths out of work overnight, we are not going to have fewer lawyers immediately. Those who can master AI will be hired and well compensated.

Anyone considering law as a profession might want to check out the one-star ratings of law firms on Yelp. Also, give these questions some thought:

• Why do so many young lawyers leave the profession?
• Why do so many attorneys become alcoholics and substance abusers?
• Why are they so disillusioned?
• Why do they have such a high divorce rate?

Instead of being a lawyer, why not become a blacksmith? At least you'll be paid for — wait, it's coming — horsing around.

Dennis Beaver practices law in Bakersfield, Calif., and welcomes comments and questions from readers, which may be faxed to (661) 323-7993, or e-mailed to Lagombeaver1@gmail.com. And be sure to visit dennisbeaver.com.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

Power semiconductors are surfing the wave of soaring AI electricity usage. Rather than moving and controlling data, power chips move and control electricity in each step that goes into converting high-voltage power from a power plant to the current that AI chips use.

"Power underpins everything in modern technology," said Leonard Shtargot, a fellow at Analog Devices, in a recent panel that brought together top industry executives. The skyrocketing amount of electricity that AI data centers use “all has to go through power semis one way or another,” said Shtargot.

Global yearly revenue for power chips will jump to $100 billion by 2029, up from about $80 billion in 2026, according to Omdia. The yearly growth rate of 7% or so is faster than previous years, with the AI segment seeing even faster growth.

Power chips are also used in EVs, smartphones, laptops, robotics, motors, wireless gear, military radar and much more. Many of the chips last for decades and have been traditionally treated as commodities, which has meant the sector hasn’t seen as much change or investment as other advanced chips, such as central processing units or graphics processing units.

Advanced power chips use high-performance, but costlier, materials such as silicon carbide and gallium nitride. The industry is also researching newer materials such as gallium oxide and diamond.

The AI industry needs power chip innovation to support the AI buildout. "I think the entire ecosystem has to evolve to meet the demand for AI end users," said Dinesh Ramanath, senior vice president at Onsemi, during the panel. He expects significant innovations in the AI market, especially in power density, or how many watts can be squeezed in a certain amount of space on a chip.

Germany’s Infineon Technologies is the industry leader with about 45% market share. The rest of the market is fragmented, with dozens of companies. Major vendors include Onsemi, STMicroelectronics, Mitsubishi Electric, Texas Instruments and Analog Devices. A big focus for chipmakers is getting power to AI chips more efficiently. For example, 10% to 15% of the high-voltage power that goes to a GPU is lost as heat, which is "not acceptable," said Jeff Halbig, product marketing manager at STMicroelectronics, during the panel.

One pressing concern is China’s push to win more of the market, including by relying more on its domestic suppliers. China already nabs 40% of global sales and Beijing is "focused on building up an ecosystem of emerging power chipmakers," noted MorningStar analyst Brian Colello in a research report last year. Other worries include cost pressure stemming from intense competition, demand volatility and worker shortages.

One way to deal with China’s effort to dominate the market is by boosting U.S.-based production, but that’s easier said than done. Industry players want more federal backing, including higher spending on research. They are also calling for efforts to ensure that chip shortages don’t become a surprise AI bottleneck.

Paul Pickering, research director at Omdia, used his presentation as a reminder about chip chaos during COVID: Cars were stuck in parking lots because they couldn’t get basic $1 chips. He wonders if in, say, 2031, there could be a data center ready to switch on, except for a missing $1 power chip and suggests that this hypothetical scenario is something that policymakers and companies can mitigate by acting early.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Once or twice a century, a single catalyst reorders the entire economic landscape: The steam engine revolution. Mass electrification. The silicon chip.

Today, it's artificial intelligence, and we're standing at the absolute baseline.

As an investor backing the architects of OpenAI, SpaceX and Figure AI, I'm often bombarded by a singular, reflexive fear: Is this a speculative bubble? Is the 2000 crash happening again?

My answer is "no." But to move past the skepticism, we must acknowledge that, unlike the dot-com era, when many of the companies were just ideas and hype, today's AI actually does useful work and generates real value.

This isn't the dot-com era

The 2000 tech bubble was practically built on fictional value. It was driven by companies that had a ".com" in their names even when they had no revenue, no profits and often no functional product. That's not what we're seeing with AI.

Look at the companies leading this shift. SpaceX, for example, handles 80% of all U.S. space launches, up from 20% a decade ago. Anduril is executing billions in signed government defense contracts. OpenAI scaled ChatGPT to 100 million users faster than any other application in history.

These are all high-revenue machines with massive market share and defensible moats. To critics focused on immediate profitability, I wish you'd recognize that history shows that transformative companies rarely go public while profitable; they prioritize scale.

The real question isn't about cash flow anymore, but who's building the essential infrastructure for the next century.

What most investors miss about valuation

When investors tell me Tesla is overvalued because of declining car sales, I ask them a question: Where do you think Apple makes most of its money? It's not selling phones. It's the App Store, taking 30% of every download, every in-app purchase, every subscription. The hardware created the platform; the platform creates the recurring revenue.

Tesla is building the same playbook. The cars are the platform. The software is the business.

• Full self-driving subscriptions at $99 per month across millions of vehicles
• Robotaxis that could operate 24/7 without labor costs

This is how you need to evaluate AI investments. Don't focus on what a company does today. Focus on what infrastructure it's building for tomorrow.

Data centers in space, which SpaceX is positioning to build, could power AI computation at a fraction of Earth-based costs because space is cooler (no expensive cooling systems) and has unlimited solar power.

The train is leaving the station

I keep hearing investors say they want to wait until things "settle down" before investing in AI. But by the time it settles down, the opportunity has passed.

Consider SpaceX's acquisition of xAI. The deal, which closed recently, brings together two of the most ambitious companies in AI and space, and they haven't even gone public yet. SpaceX's anticipated IPO is expected to raise around $75 billion at a valuation of about $2 trillion. When I decided to invest in both xAI and SpaceX through my fund, no one knew they were going to merge and become one of the biggest IPO opportunities in history.

If you're waiting for certainty, you're waiting too long. Navigating this shift requires a disciplined execution framework.

Start by auditing your current exposure. If you hold an S&P 500 index fund, nearly a third of your capital is already concentrated in the Magnificent 7. You're already an AI investor by default. It's up to you whether you have the conviction to move beyond these benchmarks into more aggressive, concentrated positions.

Growth behind closed doors

Once you decide to lean in, distinguish between your entry points. Public markets offer the safety of liquidity and access to established titans, but the most explosive growth happens behind closed doors.

Private markets, specifically venture capital and pre-IPO rounds, allow you to capture that value before a company goes public.

However, this path requires your mindset to shift to a long-game mentality, typically with seven-to-10-year horizons and capital commitments starting at $250,000.

Regardless of the entry point, you must demand fundamental proof over hype. When an AI startup crosses my desk, I move past the marketing tactics and zero in on the costly problems they're fixing and whether they have actual, validated revenue or are hiding behind a polished pitch deck.

Worthy investments should provide essential utility, not just "potential." NVIDIA, for example, dominates today because it produces the physical silicon the world needs to function.

Finally, ensure that your enthusiasm never overrides your mathematical discipline. High-growth private exposure is a powerful tool, but for the majority of investors, it should be capped at 10% to 30% of investable assets, depending on the net worth of the investor.

High conviction is not an excuse for poor risk management. You still need liquidity for your life and diversification for your protection, and your goal is to ensure you'll thrive even when the tide turns.

The real risk isn't AI — it's ignoring it

I often hear of alarmist claims that AI is coming for people's jobs. Having backed such companies as OpenAI, SpaceX and Figure AI at pivotal inflection points, here's what I'd tell you: AI won't replace you; someone using AI will.

Ten years from now, we'll look back at this moment exactly as we did the arrival of the iPhone. There will be the visionaries who recognized the shift and immediately capitalized on it, and there will be the doubters who hesitated until adaptation became a matter of pure survival.

We'll remember those who refused to let go of their Nokias or BlackBerrys while the rest of the world transitioned to the smartphone era. Perhaps they managed to stay connected, but they failed to thrive as market infrastructure evolved around them.

These massive data centers, advanced silicon, autonomous systems and space-based computing, all infrastructure currently under construction, are now the bedrock of the economy.

The companies engineering this foundation are the railroads and oil refineries of the 21st century. If you aren't building on this infrastructure, you are falling behind.

The opinions expressed in this material are provided for informational purposes only and do not constitute investment advice or an offer or solicitation to buy or sell securities. Any such offer may be made only pursuant to a confidential private placement memorandum. Investments are speculative and involve substantial risk. Past performance is not indicative of future results. Prospective investors should consult their own financial, legal, and tax advisors before investing.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

To help you understand the trends surrounding business and technology and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here's the latest…

There’s a lot happening in space these days: NASA’s ambitious moon mission, data centers in orbit, satellite cell service straight to your smartphone and the list goes on.

There are plenty of reasons to think that future business prospects, new technology and geopolitical shifts will propel the industry to new heights. The renewed optimism of satellite CEOs was clear when I attended SatShow 2026, the industry’s leading conference in Washington, D.C. The mood was in stark contrast to the last few years, when SpaceX’s disruptive force and other business woes were driving the conversations.

SpaceX is still disrupting things as a de facto monopoly, but the entire industry is growing fast and there’s more room for other players to benefit. The global space economy will reach $1 trillion in 2034, up from $626 billion in 2025, according to consulting firm Novaspace. The U.S., led by SpaceX launching 85% of spacecraft into orbit and its Starlink Internet service, reaps most of the business.

One metric that drives home the point is the surge in launch activity last year, which will continue this year and beyond. 2025 saw 325 orbital rocket launches and 4,544 spacecraft (mostly satellites) deployed, according to a global launch report by BryceTech. That marked a 25% year-over-year increase in launches and a 54% increase in spacecraft. The U.S. had 193 launches in 2025, with 165 from SpaceX alone. Second-place China registered 93.

Geopolitics are lifting space revenues

Geopolitical turmoil is spurring growth with higher defense spending and national projects for space. "Now, just given the geopolitical realities, countries are realizing that they need more than what they were buying before," said Mark Dankberg, CEO of Viasat, at SatShow. Others in the industry agreed. "The geopolitical developments that we're seeing out there are creating far and away some of the biggest commercial opportunities for Telesat and, I'll say, the rest of us," said Daniel Goldberg, CEO of Telesat.

The U.S., European countries, China and other nations want to buy more space services and own and operate their own sovereign satellites. The Pentagon has upped space outlays and will continue the spending spree. For example, the Trump administration beefed up Space Force funding for 2026 and is now requesting $71 billion for the agency in its 2027 budget proposal, an 80% jump compared with 2026.

The wars in Ukraine, Israel and Iran show how space tech is crucial for missile warning and tracking, communications, surveillance, drone and vehicle connectivity, and more. In Ukraine, SpaceX’s ability to deliver high-speed satellite internet to a small antenna on the battlefield has been pivotal. "Starlink is functionally embedded into government infrastructure," said Kimberly Burke, director of government affairs at Quilty Space, in a presentation late last year. SpaceX can expect more Pentagon contracts for its launch business, too.

"That said, the Pentagon is still wired for diversity," said Burke. Recent large U.S. military contracts have gone to Rocket Lab, HawkEye 360, York Space Systems, Sierra Space, Lockheed Martin, L3Harris and many others. Though details aren’t clear, a missile defense system known as Golden Dome, costing $185 billion-plus, also catches much industry attention.

SpaceX going public ignites investing interest

Investing in the space sector is already heating up this year, and SpaceX’s splashy upcoming initial public offering (IPO) will supercharge interest. The 24-year-old company is seeking a valuation of more than $2 trillion and aiming to raise about $75 billion.

In 2025, revenue was reportedly about $18 billion. Most revenue comes from Starlink, its speedy, space-based internet service, which has more than 10 million residential subscribers, hundreds of thousands of business subscribers and hefty defense contracts.

Upcoming risky bets include launching artificial intelligence data centers into orbit, building a full-fledged computer chip factory and getting Starship, the largest rocket ever, ready for commercial missions. SpaceX won’t have trouble spending tens of billions of dollars quickly to pursue its mission. In the near term, the top focus will be on growing its Starlink business.

SpaceX’s stock listing will bring a new wave of capital to the entire sector, including from a flood of retail investors. Investors in the space sector are bullish about SpaceX’s unprecedented stock listing. The IPO is an "inflection point" for the space industry, said Michael Mealling, general partner at Starbridge Venture Capital, at SatShow. Mark Boggett, CEO of Seraphim Space, said it will pull up valuations across the entire sector.

The heightened attention means that more Wall Street analysts will start covering the sector as space companies are included in more stock funds and more space companies go public. Investors should know that space stocks can be risky, requiring due diligence, and that the frenzy among investors could outpace the reality of individual businesses.

"I am a little concerned about public market investors looking at the space sector and not understanding the level of risk," said Mealling. “Not every company that goes public is a good company." Mealling also said that having lived through the dot-com bubble of the late 1990s, "I hope we don’t replicate that."

Upcoming battle of the two megaconstellations

As SpaceX prepares to go public, it’s just starting to see a new, fierce competitor in Amazon. Amazon’s growing constellation, Leo, will battle Starlink for customers in consumer, government and business internet markets. Starlink has some major advantages, including a huge head start, with 8,500 operational satellites, and its own rockets to launch them. Amazon is in the early stages of building a commercial business, with more than 200 satellites in orbit so far.

"The signals we get from prospective customers are incredibly strong," said Chris Weber, vice president at Amazon Leo, at the conference. Amazon is touting how it can integrate Leo with its cloud computing platform AWS. For security-minded businesses, a compelling feature is that data can travel from space to Amazon’s cloud without ever touching the internet. Besides standalone web plans, Amazon could bundle satellite service with Prime, use it to track its vast logistics network, support autonomous drone deliveries and more, according to Neil Shah, an analyst at Counterpoint.

Amazon’s space mission has taken eight years and $10 billion, and that was before the company recently acquired satellite company Globalstar for $11.6 billion to expand its network and land Apple as a customer. The competition with SpaceX spells lower prices, faster speeds and more data for consumers and businesses.

Other constellations in operation or coming soon include Eutelsat’s OneWeb, Telesat Lightspeed, Blue Origin’s TeraWave and Logos Space’s. Sovereign constellations include the European Union’s IRIS2 and China’s Guowang. The tens of thousands of planned satellites mean more demand for rockets, especially for SpaceX, which has a packed launch manifest through 2028.

Other launch vendors poised to benefit include Rocket Lab, Arianespace, Blue Origin, United Launch Alliance and Firefly Aerospace. But they don’t even come close to SpaceX’s ability to reliably launch its Falcon 9. Satellite companies, including Amazon, are desperate for other rockets to start flying regularly so SpaceX doesn’t control launch pricing. Some see Blue Origin’s reusable heavy launcher, New Glenn, as a viable option in the coming years, though the rocket company only had two launches last year. Rocket Lab ranked second in commercial launches last year with 18.

Other space trends to watch

Many companies are excited about bringing satellite connectivity directly to smartphones, no extra hardware required. The direct-to-device (D2D) service is now available on newer smartphones for sending text messages, reaching emergency services and using some low-data apps, such as mapping. The feature is useful in spots without cell service, but the industry hopes it will grow into a massive new business. SpaceX and Amazon are both spending billions of dollars to pursue D2D and will be the two leaders. Other companies working on the tech include AST SpaceMobile, Lynk Global, MDA Space and SES.

Artificial intelligence tools are exploding on the scene to analyze Earth imagery, manage airwave interference, automate in-orbit navigation, answer questions and more. Companies such as HawkEye 360 have built their own AI models from years of proprietary data to better track and identify vessels at sea. Earth imaging leader Planet says AI on the ground can parse terabytes of data and AI in space can autonomously spot methane leaks from pipelines or identify airplanes. NVIDIA AI chips are being used on satellites to process info before it hits the ground.

There’s no shortage of companies with exciting tech. Xona Space Systems is developing an alternative to GPS in low-earth orbit with centimeter-level accuracy. ISI is using AI to analyze geospatial imagery. K2 Space is working on high-power satellites for data centers in orbit. Starcloud is building space data centers and has already launched AI satellites. ICEYE uses radar pulses to produce high-resolution imagery, even through clouds and at night. SpinLaunch has a giant centrifuge concept that flings objects into orbit and is already running test launches.

Traditional hardware segments may see higher sales, too. That includes antenna systems, made by companies such as ThinKom, Intellian and Kymeta. And ground equipment, made by companies such as General Dynamics, RTX, Lockheed Martin, Kratos and Airbus.

A final thought: Space is hard

Keep in mind that space is technically challenging and hugely capital-intensive. “This is not for the faint of heart,” said Amazon Leo’s Chris Weber. “You have to have really long-term thinking.” Major concerns include rising costs, global supply chain challenges and the risk of an economic downturn.

Even in a growing industry, it’s likely that there are too many companies and some of the new business ideas won’t work out. Expect more industry consolidation, plenty of delays and occasional outright failures.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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