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Artificial intelligence is becoming large enough to affect financial stability, not only technology markets.
Andrew Bailey, Governor of the Bank of England and Chair of the Financial Stability Board, raised that concern in a letter published on August 31, 2026. The letter was sent to G20 finance ministers and central bank governors meeting in Asheville, North Carolina.
Bailey warned that financial markets remain vulnerable to a disorderly correction. He also identified frontier AI as a growing source of systemic cyber risk.
The concern is not simply that AI companies might lose value. The larger issue is how AI investment has become connected with equity markets, debt, private credit, infrastructure spending and financial institutions.
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The financial structure around AI is changing
AI investment was initially funded largely through technology companies' internal cash flows. That structure is changing.
The Bank of England reported in July that financing requirements have expanded rapidly. AI companies are increasingly using public debt, private credit, leveraged finance and structured financing to fund infrastructure.
The Bank described the current pace of AI investment as historically unusual. It also found growing dependence on external financing as data centres, computing infrastructure and energy requirements expand.
This matters because debt changes the consequences of falling expectations.
An equity investor can absorb a declining share price. A leveraged company still needs to service its debt. A highly leveraged investor may also need to sell assets quickly when prices fall.
Those connections can turn a technology-sector correction into a financial event.
Market concentration increases the transmission risk
Global stock markets have also become more dependent on AI-related companies.
The Bank of England estimated that the S&P 500 represents roughly half of global equity capitalisation. AI-related companies accounted for about half of that index by June 2026, compared with around one-quarter in 2022.
That concentration changes how an AI correction could spread.
If several major AI companies fall together, broad stock indices also decline. Pension funds, investment funds, retail investors and financial institutions holding those indices experience the same repricing.
Leverage can magnify the movement.
The Bank reported that global hedge fund equity prime-brokerage balances had risen by around 40 percent over the previous year. It also found increasing concentration in sectors associated with AI, including semiconductors.
Selling caused by falling prices can therefore create additional selling.
AI investment is becoming increasingly interconnected
Another concern involves what can be described as circular capital relationships.
Large technology companies invest in AI businesses. Those AI businesses purchase cloud computing, chips, data-centre capacity and other services from companies within the same technology ecosystem.
The Bank of England has identified these self-reinforcing capital loops as another potential source of fragility.
The system works while demand, financing and earnings expectations continue rising.
Problems emerge if investors begin questioning future AI revenue, compute demand or infrastructure requirements.
Lower expected profits can reduce valuations. Lower valuations can restrict financing. More expensive financing can reduce infrastructure investment. Reduced investment can then affect suppliers, lenders and other businesses exposed to AI spending.
That is one pathway through which a technology reassessment could reach the wider economy.
Cybersecurity creates a different form of systemic risk
Bailey's most immediate AI concern is actually cybersecurity.
The FSB said frontier models are developing stronger autonomy, problem-solving abilities and threat capabilities. These systems could change the speed, scale and economics of cyberattacks against financial institutions.
Banks are particularly exposed because financial infrastructure is interconnected.
One attack affecting a company is normally an operational problem. Simultaneous disruption across banks, payment systems or shared technology providers could become a financial-stability problem.
Dependence on a limited number of cloud, software and AI providers adds another layer. A failure affecting one widely used provider could reach many institutions at once.
This explains Bailey's call for safer model deployment, stronger recovery systems and greater resilience among critical third-party providers.
A downturn is a risk scenario, not a forecast
There is an important distinction.
Bailey is not predicting that AI will cause a global recession.
The Bank of England also recognises that AI could raise productivity and support long-term economic growth. The uncertainty concerns how quickly those gains will arrive and whether future corporate earnings will justify today's investment expectations.
Its July report examined a hypothetical severe AI repricing scenario. The scenario assumed a 45 percent decline in US equities over six quarters. The model produced a 2.2 percentage-point reduction in UK GDP through financial spillovers. It was a stress scenario, not a forecast.
That distinction defines the current debate.
AI may produce major economic gains while creating financial vulnerabilities during the investment phase.
The central question is therefore becoming less about whether AI will succeed.
It is whether markets, companies and financial institutions have built enough resilience for the possibility that AI succeeds more slowly than investors currently expect.
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