The tech giant lost roughly $67 billion in market cap in a single session, worse than Black Monday 1987, as economist Steve Hanke warns of a dual bubble in AI markets.
IBM just had the kind of day that makes corporate historians wince. On July 14, the company’s stock plunged approximately 25%, erasing roughly $67 billion in market capitalization and marking the single worst trading session in its 115-year existence. The stock fell to around $217 per share, leaving the company valued at just under $205 billion.
To put that in perspective, this was worse than IBM’s Black Monday performance in 1987, when shares dropped 23.7%.
What went wrong #
The trigger was a pre-earnings warning that landed like a grenade on trading desks. IBM disclosed that second-quarter revenue would come in at approximately $17.2 billion, well below the $17.85 billion Wall Street had penciled in.
CEO Arvind Krishna acknowledged the results were “worse than our expectations,” pointing to rising chip costs and the company’s difficulty adapting to shifting enterprise spending priorities. In English: businesses are funneling money toward AI infrastructure, and IBM isn’t catching enough of that flow.
The AI bubble question #
Economist Steve Hanke has been sounding alarms about what he calls a “dual bubble” forming in AI markets, comparing the current AI stock frenzy to the dot-com era. He’s been making this case since at least May 2026.
When Fortune reached Hanke the day after IBM’s crash, he didn’t want to dissect IBM’s specific mechanics. Instead, he pointed to something broader. “Did you see the bank earnings?” he asked, suggesting that IBM’s miss fits into a larger macroeconomic pattern that extends well beyond one company’s quarterly stumble.
What this means for crypto and digital asset investors #
IBM has been one of the more prominent legacy enterprises experimenting with blockchain technology. Its Hyperledger contributions and enterprise distributed ledger projects have served as a proof-of-concept for institutional blockchain adoption. A financially weakened IBM could scale back those investments, slowing the pace of enterprise blockchain development at a moment when supply chain and financial services applications were gaining traction.
The risk to watch is a scenario where AI disillusionment triggers a broad “risk-off” move that drags everything down simultaneously, crypto included. Investors who remember the March 2020 crash, when Bitcoin fell alongside equities before ultimately decoupling, know this playbook well.
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