By Meagen Seatter
March 4, 2026
Excerpt from article:
The tremor is fueled by software and IT companies seeing sharp drops in valuation as fears mount that AI advancements will render their core products obsolete.
Blue Owl Capital set off alarms in the private credit market, which has extended billions in financing, by selling assets across three funds and tweaking redemptions amid withdrawals tied to AI-threatened tech loans and stalled data centers. As UBS strategists recently noted, the worst-case default rate for private credit could climb as high as 15 percent as AI disrupts traditional software companies.
"There is a mechanism right now that can hurt private credit," explained Keenan Viney, a senior data scientist with Omnigence Asset Management. "Specifically for software, the AI tools have gotten exponentially better, even in just the last eight weeks. For the past year, the models have been improving, but I wasn't seeing our developers ship more software features. That has changed very suddenly.
This shift means even small teams can now build custom applications in-house, ditching the external SaaS platforms that currently carry massive amounts of private credit. In an email to INN, Viney warned that these overextended companies will face "very tough decisions" as they struggle to differentiate their software from AI-generated alternatives.
"Ultimately, if this trend continues, they will be forced into write-downs and, as our white paper discusses, private credit investors have very little protection; 70 percent of private credit loans are now covenant-lite, and when these loans default, lenders recover just US$0.57 on the dollar versus US$0.66 for covenanted loans," Viney said.
"What we really worry about is private credit funding that is specific to this tech cycle. AI infrastructure is extremely capital-intensive, with new large data centers requiring massive utility infrastructure as well. Previous tech cycles often worked on network effects, and things like social media were not compute-heavy. If the AI bet doesn't pay off or if innovations in hardware make these data centers obsolete more quickly, that creates a different (and potentially worse) transmission mechanism to the private credit markets."
As the risk profile for software-dependent loans shifts from growth to survival, capital is increasingly migrating toward the physical engines of the AI era—the high-performance hardware that remains the cycle's most resilient asset.
In the race to secure GPUs, neo-clouds - specialized providers that focus almost exclusively on high-performance AI compute - are ready to deploy the hardware powering the next generation of LLMs, but are being sidelined by underwriting processes that take months to move and equity models that demand too much control.
Investing News Network (INN) spoke with Albert Zhang, CEO at Compute Labs, along with colleagues Nikolay Filichkin and Warren Hosseinion, who argue that GPUs function better as yield-producing assets backed by contracts rather than venture capital bets or shaky private credit, describing how this shift resolves broader AI funding mismatches.
Original article here