Jamie Dimon Warns Alan Greenspan Echoes in AI Markets
Jamie Dimon said markets may be showing “too much exuberance” as alan greenspan hangs over the debate again. The JPMorgan Chase CEO pointed to frothy valuations in artificial intelligence and the Big Tech companies building its infrastructure. For investors, the warning lands in the middle of a trade that has kept pushing capital toward AI winners and the suppliers behind them.
Dimon Revives Greenspan's 1996 Warning
Dimon made the comment in a TV interview this week, and the phrase instantly recalled Greenspan’s 1996 use of “irrational exuberance.” Greenspan coined the term in a December 1996 speech at the American Enterprise Institute and asked, “How do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions?”
“We as central bankers need not be concerned if a collapsing financial asset bubble does not threaten to impair the real economy, its production, jobs, and price stability,” Greenspan said in that speech. Markets around the world sold off after the remark in December 1996, yet U.S. stocks and especially tech names kept surging for several more years before the dot-com bust.
AI Valuations Face Bubble Tests
Joachim Klement, a Panmure Liberum strategist, wrote that there are increasing signs of “irrational exuberance” in the AI boom and said, “AI is in a bubble,” though he added it can last another one to two years. His view matters because it puts a time horizon on a trade many investors have treated as if momentum alone can justify ever-higher prices.
60% is how much larger Panmure’s team says the current AI boom already is than the late-1990s technology-media-telecom episode when measured by the contribution of tech capex to U.S. GDP growth. The same team estimated that almost all of U.S. real GDP growth right now is being driven by technology investment, a concentration that leaves the broader economy leaning hard on one source of demand.
Greenspan, Bubble Memory, and Capital
1996 is the reference point that keeps coming back because it shows how long markets can ignore a warning even after a central banker uses bubble language. If AI spending keeps driving growth while valuations stay elevated, the comparison with the late-1990s cycle becomes harder for investors in megacap technology to dismiss.
That leaves readers with a simple practical check: the same companies building AI infrastructure now carry the weight of the boom, and Dimon’s warning suggests the market may already be pricing in a very long runway. For holders of AI and Big Tech exposure, the issue is not whether demand exists, but whether the current price still assumes too much of the future.
