AI disruption could spark a ‘shock to the system' in credit markets, UBS analyst says

• Baseline scenario projects combined defaults of $75-$120 billion by end of 2026 in the $1.5 trillion leveraged loan and $2 trillion private credit markets, with default rates rising by up to 2.5% and 4% respectively
• Private equity-owned software and data services companies with high debt levels are most at risk, as recent AI models from Anthropic and OpenAI have accelerated disruption timelines from 2027-2028 to immediate concerns
• A more severe 'tail risk' scenario could double the default estimates and trigger a broader credit crunch, though UBS is not yet forecasting this outcome while acknowledging the market is moving in that direction

Summary: AI Disruption Threatens Credit Markets with Potential Defaults

Key Findings:

UBS analyst Matthew Mish warns that AI disruption could trigger a "shock to the system" in credit markets, with the $3.5 trillion leveraged loan and private credit sectors most at risk. The analyst projects $75-120 billion in fresh defaults by end of 2025, driven by faster-than-expected AI adoption following recent model releases from Anthropic and OpenAI.

Market Segments:

The leveraged loan market ($1.5 trillion) could see defaults increase up to 2.5%, while private credit ($2 trillion) faces potential default increases up to 4% by late 2026. These below-investment-grade markets primarily finance private equity-backed companies with high debt levels.

Companies and Sectors:

Three categories emerge from AI disruption:

• Winners: AI creators like Anthropic and OpenAI; investment-grade software firms (Salesforce, ServiceNow) with strong balance sheets
• Losers: Private equity-owned software and data services companies carrying high debt loads

Timeline and Risks:

Market reaction has been delayed because investors underestimated disruption speed—this is "not a '27 or '28 issue," according to Mish. Recent selloffs have expanded beyond software to finance, real estate, and other sectors. A "tail risk" scenario could double projected defaults, triggering a credit crunch and broad repricing of leveraged credit.

Implications:

UBS is updating forecasts to reflect an "aggressive disruption scenario" requiring recalibration of credit evaluation methods. While not yet predicting the worst-case scenario, the firm acknowledges moving in that direction, with outcomes dependent on corporate AI adoption pace and model improvement speed.