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The stock market has been quick to punish software companies and other perceived losers from the rise of artificial intelligence in recent weeks, but credit markets are likely to be the next place where AI disruption risk appears, according to USB analyst Matthew Mish.
Tens of billions of dollars in corporate loans are likely to default over the next year as companies, especially private equity-owned software and data services companies, come under pressure from the threat of AI, Mish said in a Wednesday research note.
“We are pricing in part of what we call a rapid and aggressive disruption scenario,” Mish, head of credit strategy at UBS, told CNBC in an interview.
The UBS analyst said he and his colleagues were quick to update their forecasts for this year and beyond because the latest models from Anthropic and OpenAI have accelerated expectations about the coming of AI disruption.
“The market has been slow to react because they really didn't think it was going to happen so quickly,” Mish said. “People are having to recalibrate the whole way they evaluate credit for this disruption risk, because it's not a 27 or 28 thing.”
Investor concerns around AI boiled over this month as the market shifted from viewing the technology as a rising tide for tech companies to a winner-take-all dynamic, with Anthropic, OpenAI and others threatening incumbents. Software companies were hit first and hardest, but a continuing series of liquidations hit sectors as disparate as finance, real estate and trucking.
In their note, Mish and other UBS analysts lay out a base case in which leveraged loan and private credit borrowers will see between $75 billion and $120 billion in new defaults by the end of this year.
CNBC calculated those figures using Mish's estimates for increases of up to 2.5% and up to 4% in defaults on leveraged loans and private credit, respectively, by the end of 2026. Those are markets he estimates to be between $1.5 trillion and $2 trillion in size.
'Credit crisis'?
But Mish also highlighted the possibility of a more sudden and painful AI transition in which defaults rise to twice their baseline estimates, cutting off funding for many companies, he said. The scenario is what is known in Wall Street parlance as “tail risk.”
“The knock-on effect will be that there will be a credit crisis in the lending markets,” he said. “There will be a broad revaluation of leveraged credit and there will be a shock to the system from the credit.”
While risks increase, they will be governed by the timing of AI adoption by large corporations, the pace of improvements in AI models and other uncertain factors, according to the UBS analyst.
“We are not yet proposing that extreme risk scenario, but we are moving in that direction,” he said.
Leveraged loans and private credit are generally considered among the riskiest corners of corporate credit, as they often finance lower investment grade companies, many of them backed by private equity and with higher levels of debt.
When it comes to AI trading, companies can be classified into three broad categories, according to Mish: The first are the creators of large foundational language models like Anthropic and OpenAI, which are startups but could soon become large publicly traded companies.
The second is investment grade software companies like sales force and Adobe that have strong balance sheets and can deploy AI to defend against rivals.
The last category is the cohort of private equity-owned software and data services companies with relatively high debt levels.
“The winners of this whole transformation – if it really becomes, as we increasingly believe, a rapid, very disruptive or serious transformation – [change] “The winners are less likely to come from that third group,” Mish said.
