Jared Bernstein, a Stanford Institute for Economic Policy Research policy fellow and former Biden CEA chairman, recently offered a stark assessment of the current AI investment landscape, declaring it the third economic bubble of the century. Speaking with CNBC's "Squawk Box" hosts, Bernstein and his co-author Ryan Cummings contend that despite the genuine technological advancements and profitability of some key players, the sector exhibits classic bubble characteristics, potentially leading to a significant negative wealth effect should it burst.
Bernstein outlined several markers pointing to an AI bubble, chief among them the "rapidly rising asset prices" and "very extreme valuations" seen in the AI space. He highlighted Nvidia, trading at roughly 55 times earnings, as a prime example. More critically, he noted a historical comparison: "The share of the economy devoted to AI investment is nearly a third greater than the share of the economy devoted to internet-related investments back during the dot-com bubble." This quantitative measure suggests an unprecedented level of capital flowing into AI.
The interviewers challenged Bernstein's thesis by pointing out a significant difference from the dot-com era: many of today's leading AI companies, the "Mag 7" like Microsoft, Meta, and Amazon, are highly profitable, unlike the speculative, often profitless startups of the late 1990s. This distinction, they argued, might suggest a more robust foundation for the current AI surge.
Bernstein acknowledged the profitability of these tech giants but quickly pivoted to a crucial nuance. "You can have a bubble with completely profitable and technologically innovative firms investing into the bubble," he stated. He elaborated that the true definition of a bubble lies in "the gap between the level of speculation, the level of investment, and credible, reasonable expectations of future profits is extremely wide." For many of these companies, their vast profits stem from established business lines, ads, cloud services, e-commerce, rather than directly from their burgeoning AI investments. The AI-specific investments, he argued, represent a smaller, more speculative share of their overall financial picture.
This distinction is vital. While companies like Nvidia directly benefit from AI's infrastructure demands, the broader tech landscape's AI investments are often speculative bets on future, unproven revenue streams. Open AI, for instance, projected a trillion dollars in investment this year against only $13 billion in AI revenue. This divergence between investment scale and current AI-derived profitability fuels Bernstein's concern.