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The U.K. is at risk of recession if the artificial intelligence bubble pops, the Bank of England warned today, as investors increasingly park their cash into tech stocks.

A price correction in AI stocks, driven by a change in productivity and profitability among tech-led companies, could cause a 2.2 percent fall in U.K. GDP, the Bank warned in its financial stability report today.

“The risk of a sharp correction in equity markets remains high,” said Bank of England Governor Andrew Bailey, warning of a “triple whammy” of AI-related risks to the economy: outsized bets on AI stocks, slower adoption of the technology than predicted and questions over which firms will be winners in the sector over the long run.

However, Bailey ruled out any new regulations or policies to mitigate the financial stability risks from high valuations in the sector, instead arguing the Bank needed a greater understanding of the consequences for financial stability.

Hedge funds have piled into semiconductors and other AI-related stocks in recent months, while AI companies now make up half of the U.S. S&P 500, up from a quarter in 2022, along with rapid growth in stock markets in Taiwan and South Korea.

In addition, retail investors increasingly placing their cash in the stock market “may have added momentum to the rise in equity prices,” the Bank said, with Bailey adding that he was particularly concerned about the rapid increase in popularity of leveraged exchange-traded funds among savers.

“While UK equity indices continue to be considerably less exposed to AI companies directly, a correction in the valuation of these companies could nevertheless have a significant effect on global equity markets more generally,” said the financial stability report. “This would affect the UK macroeconomy and financial system via spillovers.”

Under the Bank’s modeling, equity market effects would account for about 36 percent of the hit to the economy, while turbulence in the bond market would account for around half.

Meanwhile, the report warned that “self-reinforcing capital loops,” where tech companies invest in AI companies that spend the money on products from the same tech companies, “increase the likelihood that a negative shock could result in a large and correlated negative earnings re-evaluation across a wider set of AI-related businesses.”

Since the Bank’s last financial stability report in December, expectations for the amount of capital expenditure from AI hyper-scalers in 2028 has grown from less than $600 billion to over a trillion dollars, according to Bloomberg data .

Morgan Stanley projects that more than half of the external financing needed for data centers from 2026 to 2028 could be funded via debt, with $700 billion coming from private credit, where there are already financial stability concerns.

“The fast growth of activity in credit markets in the first half of 2026 is resulting in potential risks building rapidly,” said the report, noting that AI hyper-scalers like OpenAI and Anthropic grew from 3 percent of U.S. investment-grade debt at the end of last year to 15 percent in May.

“Given the different funding sources from which AI companies are drawing, and different levels of transparency in those arrangements, it may be difficult for financial firms to be aware of the full extent of their direct and indirect exposures to the AI ecosystem and AI companies,” it added.

The report also warned that the risks from the massive scale of infrastructure required to sustain the AI boom were growing rapidly. An obstruction to the hardware and utilities, such as chips or electricity, could “constrain the scale and pace of build-out implies by current expectations for revenues and earnings,” with concentration among a few countries and companies compounding fears.