AI May Trigger Credit Shock: UBS

Artificial intelligence may soon rattle debt markets, not just equities. UBS credit strategist Matthew Mish warns that disruption from rapid AI adoption could spill into leveraged loans and private credit, sectors together worth roughly $3.5 trillion.

Investors have already repriced listed technology firms seen as vulnerable to automation. Mish believes lenders may be next as revenue assumptions for many borrowers come under pressure.

UBS estimates fresh defaults across the two markets could reach $75 billion to $120 billion by late 2026 under its base scenario. That implies a noticeable jump in failure rates within companies already carrying heavy debt loads.

The speed of innovation is the key variable. Breakthroughs from Anthropic and OpenAI have accelerated expectations, forcing analysts to reconsider timelines once thought years away.

Mish argues that credit investors can no longer treat AI risk as distant. If workflows and service models are replaced faster than anticipated, refinancing capacity could shrink quickly.

He also outlines a harsher possibility. In a so-called tail scenario, defaults might double, freezing capital flows and producing what traders describe as a credit crunch.

Such stress would likely lead to a broad repricing of risk, hitting private-equity-backed software and data providers hardest because of their leverage.

By contrast, firms with strong balance sheets may adapt, embedding AI defensively to protect margins and customers.

For now, UBS stops short of predicting catastrophe. But the direction of travel is clear: credit markets must begin valuing technological displacement with the same urgency equity investors already show.