What is AI Worth to the Economy?
Spending on AI is already boosting GDP, but will the massive outlays being poured into the technology deliver faster economic growth in the long run?

To help you understand what is going on in new technologies and the economy, 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 publish many (but not all) of our forecasts a few days afterward online. Here’s the latest...
Amid the hype over AI, a practical question: When will the technology boost the economy the way its developers and promoters are promising? Is artificial intelligence going to unleash a surge in worker productivity, as epochal new tech has done in the past? Or is investor enthusiasm for it overdone?
In one sense, AI is already adding to GDP. Spending on AI hardware is astronomical, both for the costly, specialized chips that power AI and the related infrastructure to deliver the electricity that those chips devour. This spending raised GDP by 0.3% in the second quarter of this year. Even that doesn’t fully capture the size of this investment surge, since some capital outlays that tech firms are making don’t show up in the official GDP accounting method. Just look at the top five firms by AI investment: Amazon, Alphabet, Meta, Microsoft and Oracle. The increase in their AI-related capital expenditures over the past two years equals about 10% of GDP gains in the U.S. over that time period. Add the power plants, transmission lines and other infrastructure they need to run their data centers, and the outlay is even bigger.
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There are also signs that businesses are gearing up for AI to make an impact on their operations. Company mentions of AI use for research tripled since Nov. 2022, when ChatGPT launched and turbocharged generative AI. 25% of job listings posted for IT professionals since the start of last year have asked for AI-related skills. The number of mobile AI app downloads hit 60 million this March. Internet searches related to AI have grown tenfold since OpenAI unveiled ChatGPT to the public. When it comes to whether AI will make workers more productive, the picture gets murkier. There are some early signs that it’s happening. Inflation-adjusted revenue per worker among S&P 500 companies has been rising since late 2022, following a 15-year period when it stayed flat.
It’s not clear why, but the overlap with advanced AI applications going mainstream is hard to ignore. But with so much money pouring into AI, there are reasons for skepticism. Much of the investment being made today could end up wasted. Many companies that are in vogue now figure to fail. It’s possible that AI computing power being rushed online could ultimately prove to be unneeded, akin to how fiber-optic cable networks got overbuilt in the 1990s. That capacity eventually got used as data consumption rose, but not before builders who spent too much on it went bankrupt. If the current AI data center boom fizzles, the pullback in spending could spark a mild recession, as the tech bust in 2001 did. Most major technological leaps take time to filter through the economy. AI does seem genuinely transformative. But the transformation may take many years.
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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David is both staff economist and reporter for The Kiplinger Letter, overseeing Kiplinger forecasts for the U.S. and world economies. Previously, he was senior principal economist in the Center for Forecasting and Modeling at IHS/GlobalInsight, and an economist in the Chief Economist's Office of the U.S. Department of Commerce. David has co-written weekly reports on economic conditions since 1992, and has forecasted GDP and its components since 1995, beating the Blue Chip Indicators forecasts two-thirds of the time. David is a Certified Business Economist as recognized by the National Association for Business Economics. He has two master's degrees and is ABD in economics from the University of North Carolina at Chapel Hill.
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