The artificial intelligence (AI) boom is disrupting industries in ways no one could have predicted, and according to UBS analyst Matthew Mish, the $3.5 trillion leverage loan and private credit markets could be next in line for a major shake-up. Mish, who heads UBS’s credit strategy, has warned that AI’s rapid development will trigger a “shock to the system” in credit markets, with tens of billions of dollars in corporate defaults expected in the near future.
In a detailed research note and interview with CNBC, Mish outlined the evolving risks that AI poses to corporate credit markets. While the stock market has been quick to react to the perceived winners and losers in the AI race—punishing software firms and traditional players in the technology space—credit markets have yet to fully account for the potential disruption. As AI models, particularly those from companies like Anthropic and OpenAI, advance at a rapid pace, the risk of defaults in the leveraged loan and private credit markets is becoming an imminent concern.
The Fast-Paced AI Revolution: Credit Markets’ Next Challenge
AI’s rapid transformation is catching many investors off guard. Mish explained that his team has had to quickly revise its forecasts for this year and beyond due to the speed at which AI technology has evolved. He noted that earlier projections were based on the assumption that AI disruption would occur later in the decade, but the latest AI models have arrived much sooner than expected. “People are recalibrating their entire approach to credit evaluation,” Mish said, referring to the need to adjust risk assessments in light of the accelerating AI-driven changes.
For the credit markets, the biggest immediate concern is the $3.5 trillion leverage loan and private credit markets. Mish and his team at UBS predict that by the end of 2026, defaults in these sectors could increase by as much as 2.5% for leveraged loans and up to 4% for private credit. These markets, which are vital for funding companies with below-investment-grade credit ratings, are already under pressure from the technological disruption brought about by AI.
Mish’s baseline scenario, outlined in the report, suggests that the leverage loan and private credit markets could experience $75 billion to $120 billion in new defaults in 2026 alone. While these numbers may seem startling, the true scale of potential defaults could be much higher in the event of a more abrupt AI-driven shift in the markets.
The Three Categories of Companies Facing AI Disruption
As AI begins to reshape industries, Mish categorizes companies into three broad groups based on how they are likely to fare in the AI revolution. The first group consists of startups developing foundational AI technologies, such as OpenAI and Anthropic. These companies are at the forefront of the AI transformation and are poised to become major players in the global economy. They have the potential to scale quickly and dominate markets, especially if their technologies become embedded in broader systems.
The second category includes investment-grade software firms, such as Salesforce and Adobe, that are financially stable and have the resources to incorporate AI into their products and services. These companies are better equipped to fend off AI-driven competition because they have strong balance sheets, customer bases, and existing market positions. They are likely to leverage AI to improve their operations, enhance product offerings, and maintain their competitive edge.
The third group consists of private equity-owned software and data services companies, many of which are heavily leveraged. These companies, often with significant debt, are particularly vulnerable to AI disruption, as they have fewer resources to quickly adapt to the changing landscape. Mish expressed skepticism about the ability of these companies to thrive in a rapidly evolving AI environment, noting that their high debt levels could make them particularly susceptible to defaults.
Rising Defaults: The Credit Crunch Scenario
As Mish and his colleagues at UBS continue to track the pace of AI’s impact on corporate credit markets, they are increasingly concerned about the potential for a sudden, sharp increase in defaults. The “tail-risk” scenario, a worst-case situation that could see defaults rise by double the expected figures, poses a significant threat to the stability of the credit markets.
In such a scenario, Mish warned, there could be a “credit crunch,” where funding becomes scarce, and the broader credit markets experience a major repricing. A rapid shift in the credit landscape could have far-reaching consequences for businesses and the financial system as a whole. Mish described the potential impact as a “shock to the system” that could reverberate through industries beyond tech and software.
The sudden rise in defaults and tightening of credit conditions could make it difficult for companies, particularly those in debt-heavy sectors, to secure financing. Mish indicated that large-scale defaults could significantly disrupt the leveraged loan and private credit markets, leading to higher borrowing costs and even more defaults as companies struggle to meet their obligations.
The Credit Market’s Slow Reaction to AI Disruption
While the stock market has already adjusted to some extent to the AI boom, the credit markets have been slower to respond. Mish suggested that the lag in credit market reactions is partly due to a delayed understanding of the speed at which AI adoption is occurring. As AI technology accelerates, investors are beginning to realize that the risks posed by AI disruption are not something to be dealt with further down the road but are already here and rapidly growing.
Mish’s research note emphasized that the markets need to account for the rapid technological shifts taking place. The financial system has yet to fully absorb the impact of AI, but it is clear that these disruptions will not be confined to the technology sector alone. Many industries will face the fallout of AI advancements, especially those with high levels of debt and underperforming business models.
Private Equity’s Role in the AI-Driven Credit Crunch
One of the primary concerns for Mish and UBS analysts is the exposure of private equity-owned companies to AI disruption. Many of these companies are highly leveraged and have been financed through private credit markets. These businesses are already under significant pressure due to high debt loads and the increasingly competitive environment created by AI advancements. As AI becomes more ingrained in industries, these companies may find themselves unable to compete with more agile, AI-driven startups and established companies that have the resources to integrate AI into their business models.
The rapid shift in the credit markets could lead to more defaults in this group of companies, with private equity firms potentially facing substantial losses. Mish noted that many of these private equity-owned companies have relied on debt to fuel growth, but AI disruption could make it much harder for them to sustain their business models in the face of competition from AI-powered innovators.
Mish’s concerns reflect a broader unease in the credit markets as investors grapple with the far-reaching implications of AI adoption. The shift toward AI-driven business models could significantly change the competitive dynamics in various sectors, from software and data services to manufacturing and finance.
The Path Forward: Navigating the AI Credit Crisis
As Canada, the U.S., and other global economies begin to embrace the full potential of AI, investors and policymakers will need to carefully monitor the impacts of this technological revolution on corporate credit markets. Mish’s warning about the potential for a “credit crunch” highlights the urgency of addressing these risks head-on. While the baseline scenario suggests moderate increases in defaults, the possibility of a more severe AI-driven disruption could dramatically reshape the credit landscape.
