Key facts
- Odds of an AI bubble bursting in 2026 have risen above 18% on the Polymarket prediction platform.
- Former Fidelity fund manager George Noble warned the fallout from an AI bubble burst could be 17 times worse than the dot-com crash.
- IBM has warned that AI infrastructure spending is drawing funds away from software, impacting revenue growth.
- US stock futures and Bitcoin saw declines amid concerns about an AI bubble.
- Memory chip stocks like SK Hynix and Samsung Electronics experienced significant drops.
The possibility of an artificial intelligence bubble bursting this year has intensified, with odds on the prediction market platform Polymarket rising above 18% for a 2026 burst. This surge in concern follows warnings from prominent figures and companies within the financial sector, including IBM and a former Fidelity fund manager.
US stock futures experienced a decline on Thursday due to renewed anxieties surrounding AI, particularly impacting memory chip stocks. SK Hynix and Samsung Electronics saw their shares plunge by nearly 9%, despite their plans for significant investments in AI and semiconductor expansion. IBM's stock also suffered a substantial drop, closing down 2.70% at $211.20 on Wednesday, extending a multi-day decline that marked its largest daily fall since 1968 and wiping out tens of billions in market value.
George Noble, a former fund manager at Fidelity, issued a stark warning, suggesting that the repercussions of an AI bubble bursting could be 17 times more severe than the dot-com crash, which erased approximately $5 trillion from the Nasdaq. He cited rising AI capital expenditure as a key concern.
Further skepticism emerged from Bank of England Governor Andrew Bailey, who indicated that an AI bubble burst could affect the UK economy and potentially necessitate an interest rate response. Other financial experts and economists have also pointed to trillions in projected AI spending as a potential trigger for such a bubble. IBM's warning specifically highlighted that substantial spending on AI infrastructure is diverting funds from software development, leading to lower-than-expected revenue growth and contributing to the recent stock price crash.