AI is no longer a distant efficiency tool for private credit portfolios; it is emerging as a direct threat to the revenue foundations of one of the market’s most heavily financed borrower classes.
Private credit markets are confronting a new and potentially structural risk as artificial intelligence tools begin to encroach on the core business models of software companies, a sector that has been central to the industry’s explosive growth over the past five years.
What was once viewed as a stable, cash-generative borrower base is now under fresh scrutiny, as investors grapple with the possibility that AI could compress margins, disrupt pricing power and weaken debt-servicing capacity across large swathes of private credit portfolios.
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The latest bout of anxiety was triggered last week after Anthropic unveiled a new generation of AI tools capable of performing complex professional and enterprise-level tasks. These are services that many software companies currently monetize through subscriptions or licensing fees. The announcement sparked a sharp sell-off in publicly listed software data providers and quickly spilled over into private markets, where concerns are harder to quantify but potentially more damaging.
According to a CNBC report, asset managers with large private credit franchises bore the brunt of investor unease. Ares Management fell more than 12% over the week, Blue Owl Capital dropped over 8%, and KKR slid close to 10%. TPG lost about 7%, while Apollo Global and BlackRock also declined. The broader equity market was comparatively calm, underscoring that investors were reacting specifically to perceived risks within private credit rather than to a general market shock.
At the heart of the concern is the private credit market’s deep exposure to software and technology borrowers. Since around 2020, enterprise software has been one of the most favored sectors for private lenders, prized for its recurring revenues, high margins, and perceived resilience to economic cycles. PitchBook noted that many of the largest unitranche loans on record — a structure combining multiple debt tranches into a single, often highly leveraged instrument — have been extended to software and tech companies.
According to PitchBook data, software accounts for roughly 17% of U.S. business development companies’ investments by deal count, second only to commercial services. That concentration leaves private credit particularly vulnerable if AI adoption accelerates faster than software firms can adapt their products, pricing, and cost structures.
“Private credit loans to a lot of software companies,” said Jeffrey C. Hooke, a senior lecturer in finance at Johns Hopkins Carey Business School. “If they start going south, there’s going to be problems in the portfolio.”
Analysts warn that AI-driven disruption could unfold differently from past technology shifts. Rather than simply creating new demand, advanced AI tools may directly substitute for software products, eroding revenues without a clear transition period. That raises the risk of sudden cash-flow deterioration, especially for mid-sized, sponsor-backed software firms that rely on steady subscription income to service debt.
UBS Group has modelled an aggressive disruption scenario in which default rates in U.S. private credit climb to 13%. That compares with stressed default estimates of about 8% for leveraged loans and 4% for high-yield bonds, highlighting how exposed private credit could be in a severe downturn tied to technological change rather than a traditional recession.
The risk is compounded by structural features of the private credit market itself. Unlike public debt, private loans are illiquid and infrequently marked to market, making it difficult for investors to assess stress in real time. Loan extensions, amendments, and payment deferrals can mask underlying weakness, sometimes for years.
Hooke said many of these issues existed well before the latest AI concerns. He pointed to persistent problems around liquidity, refinancing risk, and valuation opacity, arguing that AI has merely added pressure to a market already showing signs of strain.
Those warnings echo broader concerns raised by senior figures in global finance. JPMorgan Chase CEO Jamie Dimon cautioned last year that problems in private credit often resemble “cockroaches,” where the appearance of one issue suggests others may be lurking unseen. The fear among investors now is that AI could be the catalyst that exposes hidden fragilities across portfolios.
Kenny Tang, head of U.S. credit research at PitchBook LCD, said AI disruption will not affect all software borrowers equally. Some firms are likely to integrate AI into their offerings and strengthen their competitive position, while others — particularly those selling narrowly defined or easily replicable services — may struggle.
“AI disruption could be a credit risk for private credit lenders for some of its Software & Services sector borrowers and perhaps not for others,” Tang said, adding that outcomes will depend on how quickly companies adapt.
One area drawing particular scrutiny is the prevalence of payment-in-kind loans in the software sector. These arrangements allow borrowers to defer interest payments by capitalizing them into the loan principal. While PIK structures are often justified by growth expectations, they can become dangerous if revenues falter. Software and services companies represent the largest share of PIK loans, according to PitchBook, increasing the risk that deferred interest snowballs into unsustainable debt burdens if AI competition intensifies.
Moody’s Analytics chief economist Mark Zandi described the combination of rapid private credit growth, rising leverage, and limited transparency as clear warning signs. While he said the industry may be able to absorb losses in the near term, he warned that capacity could be tested if credit expansion continues at its current pace.
“There will surely be significant credit problems,” Zandi said, noting that today’s resilience may not hold if stresses accumulate over time.
Some private credit managers have moved to reassure investors. Ares Management CEO Michael Arougheti said the firm’s exposure to software is relatively modest, with software loans making up about 6% of total assets and less than 9% of private credit assets under management. He said Ares focuses on profitable software businesses with strong cash flow and conservative leverage, helping keep problem loans near zero.
Still, the broader sell-off suggests investors are reassessing assumptions that underpinned years of private credit expansion. As AI tools grow more capable and more widely deployed, they are forcing lenders and investors to confront a difficult question: Will the sector’s reliance on software borrowers remain a strength, or is it becoming a concentrated risk?
In a market built on long-dated, opaque loans, the speed of AI-driven change may prove to be its most unsettling feature.