The stock market has already begun to reflect the potential impact of artificial intelligence, punishing companies seen as lagging in the AI race. But a new analysis from UBS suggests the disruption from AI could soon extend beyond equities, potentially triggering significant defaults in the $3.5 trillion leveraged loan and private credit markets. The firm’s head of credit strategy, Matthew Mish, warns that the pace of AI development is accelerating, and the credit markets are largely unprepared for the speed of the coming changes.
Mish and his team at UBS now anticipate between $75 billion and $120 billion in defaults across these markets by the end of 2026, a substantial increase driven by the threat AI poses to companies, particularly those in the software and data services sectors backed by private equity. This assessment comes as investors reassess AI’s impact, shifting from a view of broad benefits to a “winner-take-all” dynamic where established companies face disruption from innovators like Anthropic, and OpenAI. The shift in sentiment has already been visible in recent sell-offs affecting not just technology firms, but also sectors like finance, real estate, and trucking.
AI’s Rapid Advance and the Credit Risk
The speed of AI’s evolution is at the heart of Mish’s concerns. He explained that recent advancements in AI models from companies like Anthropic and OpenAI have forced a rapid recalibration of forecasts. “The market has been gradual to react because they didn’t really consider it was going to happen this prompt,” Mish told CNBC. “People are having to recalibrate the whole way that they look at evaluating credit for this disruption risk, because it’s not a ’27 or ’28 issue.”
The potential for widespread defaults isn’t simply a matter of technological obsolescence. Mish highlights a “tail risk” scenario – a more abrupt and painful transition where defaults could double, effectively freezing funding for many companies. This could lead to what he describes as a “credit crunch” in loan markets, forcing a broad repricing of leveraged credit and a systemic shock to the financial system. While this scenario isn’t UBS’s base case, Mish emphasized they are “moving in that direction.”
Which Companies Are Most Vulnerable?
Leveraged loans and private credit are already considered riskier segments of the corporate credit landscape, often financing companies with significant debt loads and lower credit ratings, frequently backed by private equity firms. According to Mish, companies can be broadly categorized based on their position in the AI landscape. The first group comprises the creators of foundational large language models, such as Anthropic and OpenAI, which, while currently startups, have the potential to become major publicly traded companies.
The second category consists of established, investment-grade software firms like Salesforce and Adobe, which possess robust balance sheets and the capacity to integrate AI to maintain their competitive edge. However, the most vulnerable group is the cohort of private equity-owned software and data services companies burdened with high levels of debt. “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 stated.
The Broader Economic Implications
The potential for widespread defaults in the leveraged loan and private credit markets raises concerns about broader economic consequences. These markets play a crucial role in financing corporate activity, and a significant contraction in lending could stifle investment and growth. The situation is further complicated by the fact that many of these loans are held by non-bank lenders, which may be less regulated and have less access to liquidity than traditional banks.
Matthew Mish, a UBS analyst based in New York with over 500 connections on LinkedIn, according to his LinkedIn profile, emphasizes that the timing of AI adoption by large corporations and the continued pace of AI model improvements will be key factors determining the severity of the impact. The situation remains fluid, and the market is still grappling with the implications of this rapidly evolving technology.
The next key data point to watch will be corporate earnings reports in the coming months, which will provide a clearer picture of how companies are navigating the challenges and opportunities presented by AI. Investors and analysts will be closely scrutinizing these reports for signs of stress in the leveraged loan and private credit markets.
What we have is a developing story. Share your thoughts in the comments below.
