AI Shock Could Reshape Credit Markets, Says UBS Analyst
The Impact of AI on Leverage Loans and Private Credit Markets
The $3.5 trillion leverage loans and private credit markets may soon face disruption due to the rapid advancements in artificial intelligence, according to UBS analyst Matthew Mish. He has noted that the transformation brought about by AI is occurring faster than previously anticipated.
Mish predicts that between $75 billion and $120 billion in fresh defaults could occur in these two markets by the end of this year. This forecast comes as the stock market has already started punishing software firms and other companies seen as potential losers in the AI boom. However, Mish believes that the credit markets will be the next area where the risks of AI disruption become apparent.
According to Mish, tens of billions of dollars in corporate loans are expected to default over the next year, particularly affecting software and data services firms owned by private equity. These companies are under pressure due to the threat posed by AI. In a recent research note, Mish mentioned that he and his colleagues have been updating their forecasts because the latest models from Anthropic and OpenAI have accelerated expectations for AI disruption.
"The market has been slow to react because they didn't really think it was going to happen this fast," Mish said. "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."
Investor concerns around AI have intensified this month as the market shifted from viewing the technology as a rising tide story for tech companies to a more winner-take-all dynamic. Companies like Anthropic and OpenAI are now seen as threats to incumbents. Software firms were hit first and hardest, but a series of sell-offs affected sectors as diverse as finance, real estate, and trucking.
In his note, Mish and other UBS analysts outlined a baseline scenario in which borrowers of leveraged loans and private credit would see a combined $75 billion to $120 billion in fresh defaults by the end of this year. These figures were calculated using Mish’s estimates for increases of up to 2.5% and up to 4% in defaults for leveraged loans and private credit, respectively, by late 2026. These are markets estimated to be $1.5 trillion and $2 trillion in size.
The Possibility of a 'Credit Crunch'
Mish also highlighted the possibility of a more sudden and painful AI transition, where defaults could jump by twice the estimates for his base assumption. This scenario, known as a "tail risk" in Wall Street jargon, could lead to a credit crunch in loan markets. It would result in a broad repricing of leveraged credit and a shock to the system coming from credit.
While the risks are increasing, they will depend on factors such as the timing of AI adoption by large corporations, the pace of AI model improvements, and other uncertain elements. Mish stated that they are not yet calling for the tail-risk scenario, but they are moving in that direction.
Leveraged loans and private credit are generally considered riskier corners of corporate credit since they often finance below-investment-grade companies. Many of these companies are backed by private equity and carry higher levels of debt.
Categories of Companies Affected by AI
When it comes to the AI trade, companies can be divided into three broad categories, according to Mish:
- Creators of foundational large language models such as Anthropic and OpenAI, which are startups but could soon become large, publicly traded companies.
- Investment-grade software firms like Salesforce and Adobe that have robust balance sheets and can implement AI to fend off challengers.
- Private equity-owned software and data services companies with relatively high levels of debt.
"The winners of this entire transformation — if it really becomes, as we're increasingly believing, a rapid and very disruptive or severe [change] — the winners are least likely to come from that third bucket," Mish said.
