The stock market’s recent reckoning with artificial intelligence may be just the opening act. Credit markets, encompassing a massive UBS estimate of $3.5 trillion in leveraged loans and private credit, are poised to feel the disruptive force of AI, potentially triggering a wave of corporate loan defaults.
According to Matthew Mish, head of credit strategy at UBS, the speed of AI’s advancement has caught the market off guard. “The market has been slow to react because they didn’t really think it was going to happen this fast,” Mish told CNBC. He now anticipates between $75 billion and $120 billion in fresh defaults by the end of , concentrated among companies vulnerable to AI-driven disruption.
A Shift in Perception
The initial market reaction to AI focused on the potential for broad technological gains. However, sentiment has shifted dramatically in recent weeks, with investors increasingly recognizing a “winner-take-all” dynamic. Companies like Anthropic and OpenAI are now seen as potential disruptors to established industry leaders, leading to sell-offs not just in software, but also in sectors like finance, real estate, and trucking. This shift in perception is accelerating the timeline for disruption, according to UBS.
The companies most at risk are those in the software and data services industries, particularly those owned by private equity firms and burdened with significant debt. Mish categorizes companies into three groups: those developing foundational AI models, investment-grade software firms with strong balance sheets capable of adapting to AI, and the heavily indebted, private equity-backed firms facing the greatest threat. It is this last group that is expected to bear the brunt of the defaults.
The Potential for a ‘Credit Crunch’
UBS’s analysis suggests a baseline scenario of increased default rates, but also highlights a “tail risk” – a more sudden and severe AI transition that could double the estimated default rates. This scenario could trigger a broader “credit crunch,” characterized by a tightening of lending standards and a significant repricing of leveraged credit. “The knock-on effect will be that you will have a credit crunch in loan markets,” Mish warned. “You will have a broad repricing of leveraged credit, and you will have a shock to the system coming from credit.”
Leveraged loans and private credit are already considered riskier segments of the corporate credit market, as they typically finance companies with lower credit ratings and higher debt levels. The added pressure from AI disruption could exacerbate existing vulnerabilities.
Sector Breakdown and Winners & Losers
UBS estimates that technology accounts for roughly 24% of holdings in Business Development Company (BDC) portfolios, while business services represent around 30%. This concentration underscores the potential for widespread impact across these sectors.
According to Mish, the companies poised to benefit most from the AI revolution are those creating the foundational large language models, such as Anthropic and OpenAI. Investment-grade software firms like Salesforce and Adobe, with their robust balance sheets and capacity for innovation, are also expected to navigate the transition successfully. However, the future looks considerably more challenging for the heavily indebted, private equity-backed software and data services companies.
“The winners of this entire transformation — if it really becomes, as we’re increasingly believing, a rapid and very disruptive [change] — the winners are least likely to come from that third bucket,” Mish said.
The timing of AI adoption by large corporations and the continued pace of AI model improvements remain key uncertainties. While UBS is not yet predicting the more severe “tail risk” scenario, the firm acknowledges that the situation is evolving rapidly and warrants close monitoring. The potential for significant defaults in the leveraged loan and private credit markets represents a growing concern for investors and lenders alike, signaling that the AI revolution is extending its reach far beyond the technology sector.
