The dot-com era offers a useful lens on today’s AI boom—but not a crystal ball. In an August 2025 Forbes article, Harvard research fellow Paulo Carvão argues that history points to genuine risks without proving that an AI crash is imminent.
One clear parallel is market concentration. At the time of publication, the “Magnificent Seven” represented more than a third of the S&P 500. At the dot-com peak in 2000, five prominent technology stocks made up 15% of the index. Such concentration can make markets vulnerable, Carvão argues, but it does not by itself mean a crash is inevitable.
The infrastructure buildout offers another caution. During the dot-com boom, companies invested heavily in fiber-optic networks before demand arrived quickly enough to support the spending; bankruptcies followed. Today, leading AI companies are pouring money into data centers, raising a familiar question: will demand justify the investment?
Yet the earlier buildout also left behind infrastructure that later helped support the internet economy, application businesses and cloud computing. Carvão suggests AI data centers could likewise prove useful over time—but presents that as a possibility, not a guaranteed payoff.
The strongest case for AI’s broader significance may come from its adoption. The article cites a National Bureau of Economic Research survey reporting that, by late 2024, about 40% of the U.S. population had used generative AI, while 23% had used it for work at least once in the previous week. The study also found that workplace adoption was progressing faster after launch than adoption of personal computers or the internet.
Those figures point to AI’s potential to become a consequential, general-purpose technology. They do not settle whether today’s valuations are justified or whether data-center investments will earn adequate returns.
That is the careful lesson in Carvão’s comparison: the dot-com story is a warning about concentrated markets and infrastructure built ahead of demand, not a timetable for an AI collapse. Even if a market correction comes, the technology’s lasting value could outlive it.
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