OXFORD – When OpenAI recently committed $1.4 trillion to securing future computing capacity, it was merely the latest indication of irrational exuberance in 2025. By some estimates, US GDP growth in the first half of this year came almost entirely from data centers, prompting a flood of commentary about when the bubble will burst and what it may leave behind. While the late 1990s dot-com party ended with a hangover for Wall Street, Main Street kept what mattered: the infrastructure. Productivity rose, and the fiber laid during the boom years still works today. US President Bill Clinton’s vow to build a “bridge to the 21st century” was one of those rare campaign promises that is actually fulfilled.
Today’s AI investments could well pay off like the internet did. For now, though, the gains look more muted, and the macro downsides larger, than in the case of the dot-com bubble. Consider the potential benefits. In the late 1990s, the internet’s payoff showed up while the bubble was still inflating: US labor productivity growth averaged about 2.8% from 1995 to 2004, roughly double the previous two decades’ pace, before fading in the mid-2000s. You could see the gains in the national accounts even as Pets.com was buying up its ill-fated Super Bowl ads.
This time, US labor productivity growth has picked up after two sluggish decades – reaching around 2.7% last year – but it’s too soon to say that AI is the reason. In fact, AI adoption is slipping, with a recent US Census Bureau survey showing lower use among large firms. If the recent uptick in productivity was mostly an AI story, it could be expected to fade as adoption ebbs – another reminder of how fleeting these waves can be. As visible as the 1990s information-technology boom was in real time, it petered out within a decade or so.
It is tempting to think that large language models (LLMs) will speed up innovation and discovery itself, such as by surfacing hidden links in the academic literature, writing code, and drafting protocols. New tools – from Robert Hooke’s microscope to Galileo’s telescope – have sparked such leaps before. This time, however, we have already had the ultimate research tool in the form of the internet-connected PC. Yet even with instant access to the world’s accumulated knowledge and top talent, measures of research productivity and breakthrough innovation have declined. Keeping alive Moore’s Law – the observation that computer processing power doubles every two years – now takes orders of magnitude more researchers than it did in the early 1970s.
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