The recent selloff in credit markets reflects growing concern that artificial intelligence (AI) is moving faster than many expect, and its impact may extend well beyond software, according to UBS analysts.
In a note to clients, the bank’s analysts said markets have only partially priced in the risk, particularly for lower-quality credit sectors in the US. Investment-grade (IG) bonds, by contrast, are likely to hold up thanks to stronger balance sheets and stable credit ratings.
The timing of AI disruption is coming into sharper focus, UBS said, with changes expected in quarters rather than years. But how quickly disruption hits will depend on factors such as enterprise adoption of AI, sector-level refinancing needs, and market pricing.
UBS estimates that 10 to 15% of US IG bonds are exposed to disruption, primarily in consumer non-cyclical sectors like healthcare, and that high-yield (HY) and leveraged loan (LL) markets—especially in US tech—face greater risks. Analysts forecast modest increases in defaults by late 2026: roughly 0.5 to 1% for HY bonds, 1.5 to 2.5% for loans, and 2.5 to 4% for private credit.
The commentary also suggests that the market is in the early stages of pricing in AI disruption for most sectors. Tech loans are likely in the third or fourth inning of pricing, while non-tech HY and LL markets are still in the early innings.
UBS predicts 3 to 5% total returns for US credit markets in 2026, with IG bonds expected to outperform HY and loan markets. The firm cautioned that while the scenario is not overly pessimistic, indirect effects of AI disruption, such as tighter credit conditions, could amplify risks across other sectors, potentially affecting broader markets and corporate investment plans.
“Credit markets are a key source of funding for AI-driven growth,” analysts wrote. “If losses spike too quickly in loan markets, it could slow capital spending and undercut the AI boom itself.”