The Best AI ETFs to Buy

The best AI ETFs provide investors access to a world-changing AI megatrend. But exposure, cost and risk can vary greatly.

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The Global Industry Classification Standard (GICS) places information technology into three industry groups: software and services, technology hardware and equipment, and semiconductors and semiconductor equipment

In 2025, what ties these groups together is their role in developing, advancing, and commercializing artificial intelligence (AI) applications.

For the average person, AI today is less about science fiction and more about practical tools. It powers voice assistants, creates personalized shopping suggestions, improves medical imaging, automates customer service and helps design computer chips and software.

While entrepreneurs like Sam Altman of OpenAI or Elon Musk of xAI often speak about AI as a transformative force for society, most of its present use-cases remain focused on making existing technologies faster, cheaper and more efficient.

Because many of the companies driving this trend are publicly traded, a growing number of thematic exchange-traded funds (ETFs) have emerged to provide access.

Thematic ETFs focus on a specific theme, such as AI, rather than a broad sector or market index. This makes them different from traditional sector funds or index funds, which cast a wider net and hold companies across an entire industry or market.

Understanding AI as an investor

It's easy to get lost in the details if you approach AI investing by trying to understand what the technology is capable of.

New large language models roll out quickly, and disruption means today's leader could be tomorrow's laggard. Unless you have a technical or scientific background, parsing whitepapers and research can feel overwhelming.

For most investors, a more practical approach is to view the AI ecosystem holistically. That means following where the money is going and identifying which companies can embed themselves at each stage of the value chain.

This mindset also requires discarding traditional sector boundaries, since AI-related companies are not confined to technology stocks. They also show up as communication services stocks, consumer discretionary stocks, even real estate stocks.

Technology: Microsoft (MSFT), Nvidia (NVDA), Oracle (ORCL) and CoreWeave (CRWV) provide the software, chips and cloud infrastructure that power AI.

Communications: Alphabet (GOOGL) and Meta Platforms (META), though classified here rather than technology, embed AI in search, social media and digital advertising.

Consumer discretionary: Amazon.com (AMZN) applies AI to e-commerce, logistics, and cloud services, while Tesla uses it in autonomous driving.

Real estate: Data center REITs such as Equinix (EQIX) and Digital Realty (DLR) supply the physical infrastructure needed to support AI’s computing demands.

AI ETFs are designed to give investors exposure across this ecosystem. Many use index-based benchmarks that apply rules to sift through potential holdings, whether by measuring the percentage of revenue tied to AI or even scanning earnings reports for mentions of AI.

Others are actively managed, relying on analyst teams to apply discretion and, increasingly, using AI tools themselves to process information more efficiently.

How we picked the best AI ETFs

For AI thematic ETFs, we included both passive and active funds.

While S&P's SPIVA scorecards show many active managers underperforming broad stock and bond benchmarks, that data mostly covers traditional style categories like value, growth or small- and large-cap. Comparable long-term performance data for AI ETFs doesn't exist yet.

Another reason to consider active funds is that many passive, index-based AI ETFs charge expense ratios similar to their active peers.

Since the segment is narrow and diversification is hard to achieve, the active-vs-passive distinction is less critical for investors here.

We did, however, set a fee cap. Only ETFs with expense ratios at or below 0.75% made the list. On a $10,000 investment, that equals $75 in annual fees.

These costs aren't paid upfront but deducted gradually, reducing net returns over time. This is generally the standard for active ETFs and should not be exceeded for index-tracking ETFs.

Liquidity was another key factor. Large-cap U.S. AI companies trade actively, but smaller and foreign stocks often do not.

Because ETF liquidity depends on the liquidity of the underlying holdings, we prioritized ETFs with a 30-day median bid-ask spread of 0.1% or less.

Finally, we screened for scale. The ETF industry is highly competitive, with small and large issuers alike launching new AI funds to capture investor attention. Not all will survive.

Funds below $50 million in assets under management face higher closure risk, so we limited our picks to those above this threshold.

Tony started investing during the 2017 marijuana stock bubble. After incurring some hilarious losses on various poor stock picks, he now adheres to Bogleheads-style passive investing strategies using index ETFs. Tony graduated in 2023 from Columbia University with a Master's degree in risk management. He holds the Certified ETF Advisor (CETF®) designation from The ETF Institute. Tony's work has also appeared in U.S. News & World Report, USA Today, ETF Central, The Motley Fool, TheStreet, and Benzinga. He is the founder of ETF Portfolio Blueprint.