When Silicon Valley's visionaries and Wall Street's gatekeepers simultaneously acknowledge a bubble, everyone should listen.

Jeff Bezos, the founder of Amazon, recently described the Artificial Intelligence (AI) boom as an "industrial bubble" at the Italian Tech Week, though he insists the technology is "real" and will bring "gigantic" societal benefits. Open AI founder Sam Altman has been even more candid, acknowledging the "insane" valuations and admitting that investors are "overexcited about AI," warning that people will "get very burnt."

The AI Bubble Paradox
Yet, the chorus of warnings—from Bezos and Altman in tech to David Solomon at Goldman Sachs and Jamie Dimon at JP Morgan—comes with a curious twist: none of them are pulling back.
The concerns are mounting from multiple fronts. Goldman Sachs CEO David Solomon warned at the same Italian Tech Week that AI's rapid acceleration is driving capital formation that could push valuations beyond sustainable fundamentals, while Solomon noted that "there will be a lot of capital that was deployed that didn't deliver returns" and emphasised "it's not different this time".

JP Morgan's Jamie Dimon described himself as "far more worried than others" about an AI-driven market boom that could mirror the dot-com crash. Morgan Stanley's top analyst Lisa Shalett expressed being "very concerned" about AI's grip on markets, noting the prominence of private equity and debt capital "tends to produce bubbles, because it may be unspoken-for capacity".

The numbers justify their alarm. Microsoft plans to spend $80 billion on AI data centers this fiscal year, while Meta projects up to $72 billion in AI infrastructure investments. Just five AI hyperscalers are projected to spend over $1 trillion collectively by 2027. The concentration is staggering: AI companies have accounted for 75 percent of S&P 500 gains, 80 percent of profits, and a shocking 90 percent of capital expenditures.