This article is about the coming collapse of a particular economic bubble but I also think it is emblematic of a broader process of collapse too. It is very telling about our future how FAR from reality our thinking has gotten about AI.
In the study, published in July, the think tank Model Evaluation & Threat Research randomly assigned a group of experienced software developers to perform coding tasks with or without AI tools. It was the most rigorous test to date of how AI would perform in the real world. Because coding is one of the skills that existing models have largely mastered, just about everyone involved expected AI to generate huge productivity gains. In a pre-experiment survey of experts, the mean prediction was that AI would speed developers’ work by nearly 40 percent. Afterward, the study participants estimated that AI had made them 20 percent faster.
But when the METR team looked at the employees’ actual work output, they found that the developers had completed tasks 20 percent slower when using AI than when working without it. The researchers were stunned. “No one expected that outcome,” Nate Rush, one of the authors of the study, told me. “We didn’t even really consider a slowdown as a possibility.”
No individual experiment should be treated as the final word. But the METR study is, according to many AI experts, the best we have—and it helps make sense of an otherwise paradoxical moment for AI. On the one hand, the United States is undergoing an extraordinary, AI-fueled economic boom: The stock market is soaring thanks to the frothy valuations of AI-associated tech giants, and the real economy is being propelled by hundreds of billions of dollars of spending on data centers and other AI infrastructure. Undergirding all of the investment is the belief that AI will make workers dramatically more productive, which will in turn boost corporate profits to unimaginable levels.
On the other hand, evidence is piling up that AI is failing to deliver in the real world. The tech giants pouring the most money into AI are nowhere close to recouping their investments. Research suggests that the companies trying to incorporate AI have seen virtually no impact on their bottom line. And economists looking for evidence of AI-replaced job displacement have mostly come up empty.
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The capability-reliability gap might explain why generative AI has so far failed to deliver tangible results for businesses that use it. When researchers at MIT recently tracked the results of 300 publicly disclosed AI initiatives, they found that 95 percent of projects failed to deliver any boost to profits. A March report from McKinsey & Company found that 71 percent of companies reported using generative AI, and more than 80 percent of them reported that the technology had no “tangible impact” on earnings.
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What makes the current situation distinctive is that AI appears to be propping up something like the entire U.S. economy. More than half of the growth of the S&P 500 since 2023 has come from just seven companies: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. These firms, collectively known as the Magnificent Seven, are seen as especially well positioned to prosper from the AI revolution.
That prosperity has largely yet to materialize anywhere other than their share prices.
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The dot-com crash was bad, but it did not trigger a crisis. An AI-bubble crash could be different. AI-related investments have already surpassed the level that telecom hit at the peak of the dot-com boom as a share of the economy. In the first half of this year, business spending on AI added more to GDP growth than all consumer spending combined. Many experts believe that a major reason the U.S. economy has been able to weather tariffs and mass deportations without a recession is because all of this AI spending is acting, in the words of one economist, as a “massive private sector stimulus program.” An AI crash could lead broadly to less spending, fewer jobs, and slower growth, potentially dragging the economy into a recession. The economist Noah Smith argues that it could even lead to a financial crisis if the unregulated “private credit” loans funding much of the industry’s expansion all go bust at once.
