Why AI Could Jolt Private Credit—And How Savvy Investors Can Profit

• UBS flags up to 35% of private‑credit exposure to AI risk – but the panic may be overstated.
• Private‑credit lenders hold 24% of their assets in software firms, yet most loans have 5‑year maturities that cushion short‑term shocks.
• Equity investors feel the pain of revenue erosion; lenders often still collect contractual cash flow.
• Private‑equity firms have $1.7 trillion of dry powder to rescue stressed software assets.
• Historical restructurings show recovery rates of 60‑80% for senior secured loans, even in deep downturns.

You’re watching AI headlines, but your private‑credit portfolio isn’t on the brink of disaster.

Why Private Credit’s AI Risk Is Misread by the Market

UBS’s recent note warned that as much as 35% of private‑credit portfolios could face “elevated risk” from artificial‑intelligence disruption. The headline caught the momentum crowd off‑guard, prompting redemptions at funds like Blue Owl’s retail‑focused vehicle and a sell‑off in software stocks such as CrowdStrike. The narrative assumes that a future AI wave will instantly erase the cash‑flow streams that private‑credit loans depend on. In reality, lenders are betting on a company’s ability to meet scheduled debt service, not on perpetual equity upside.

How Software Lenders Actually Manage AI‑Driven Stress

When a business‑development company (BDC) or a private‑credit fund issues a loan to a mid‑market software firm, the loan contract typically spans five years. This “duration” window gives sponsors ample runway to:

• Implement cost‑cutting initiatives.
• Inject growth capital or acquire complementary technology.
• Negotiate strategic sales that preserve cash‑flow while transferring equity risk.

Even if AI erodes a software vendor’s top line, the decline is gradual—often over multiple fiscal years. Lenders continue to receive interest and principal payments until the maturity date, at which point the loan is either refinanced, repaid, or rolled into a restructuring that still recovers a sizable portion of the claim.

What History Teaches About Tech Disruption and Credit

The tech‑sector credit cycle has survived several paradigm shifts—think of the dot‑com bust, the rise of cloud computing, and the 2020 pandemic acceleration of SaaS adoption. In each case, senior secured lenders recorded recovery rates between 60% and 80% of face value, even when equity investors saw near‑total write‑downs.

For instance, during the 2008‑09 crisis, distressed software lenders restructured more than 150 deals, yet the aggregate loss on senior secured paper remained well below 30%. The key driver was the contractual priority of debt, which forces borrowers to allocate cash‑flow to service obligations before any equity payout.

Sector‑Wide Implications: From BDCs to Big‑Cap Private‑Equity

Business‑development companies sit at the intersection of public markets and private credit. Their portfolios are weighted heavily toward software (≈24%) because recurring subscription revenues fit well with the cash‑flow profile lenders desire. However, the same sponsors that underwrite the loans also sit on the equity side, creating a natural hedge.

Private‑equity giants such as Blackstone and KKR hold roughly $1.7 trillion in unfunded commitments—dry powder that can be deployed to support stressed software assets. When a portfolio company shows early signs of AI‑related churn, a PE sponsor may:

• Accelerate operational turnarounds.
• Provide bridge financing to extend the loan horizon.
• Package the business for sale to a strategic buyer who values customer relationships more than the underlying technology.

These actions typically preserve the senior loan’s value, turning a potential default into a controlled exit.

Investor Playbook: Bull vs. Bear Cases on Private Credit Exposure

Bull Case

• AI disruption unfolds slower than the average 5‑year loan term, allowing borrowers to meet debt service.
• Private‑credit managers tighten underwriting standards, favoring higher‑quality software borrowers with strong cash‑flow coverage.
• Historical recovery rates (60‑80%) remain a realistic floor, keeping absolute loss expectations modest.
• PE dry‑powder injections and strategic sales create “soft landings” for distressed assets, protecting senior debt.

Bear Case

• AI accelerates revenue loss to a point where borrowers cannot meet interest covenants before maturity.
• Widespread portfolio concentration in mid‑market software amplifies sector‑specific shocks.
• Refinancing risk spikes if credit markets tighten further, forcing lenders into distressed‑sale pricing.
• Recovery rates plunge below historical norms due to simultaneous equity wipe‑outs and weakened sponsor support.

For most investors, the bull scenario is more probable because the market is already pricing a near‑total collapse—a view that ignores the mechanics of loan contracts, sponsor incentives, and the time lag inherent in technology adoption.

Bottom Line: Time, Not Panic, Is the Real Risk Manager

Private‑credit exposure to software will naturally wind down as existing loans mature. If managers truly feared an AI‑induced credit implosion, the simplest response would be to stop originating new software loans and let the current book run its course. The current sell‑off reflects a mis‑interpretation of credit risk as equity risk.

Investors who focus on manager quality, loan duration, and covenant strength can capture the attractive risk‑adjusted returns that private credit historically delivers, while the market over‑reacts to headline‑driven AI hype.