AI Shock Tests $3tn Private Credit Market as Software Rout Exposes Concentration Risk

NEW YORK —
A fresh wave of concern has rippled through private credit markets as investors and asset managers reassess how loans to software companies will perform if artificial intelligence permanently compresses revenues, shortens product life cycles, or reduces the buyer pool for distressed assets. The private-credit ecosystem has grown rapidly into a multitrillion-dollar set of markets that underwrite buyouts, growth-stage financings, specialty finance and mezzanine loans, and observers warn that concentrated exposure in a sector undergoing rapid structural change could magnify losses for certain vehicles and produce outsized mark-to-market effects for publicly traded credit wrappers. The immediate question for institutional investors is how to measure not just headline exposure to “software” but the underlying revenue durability, covenant protection and liquidity profile of each loan.

Private credit expanded as banks pulled back from certain leveraged and middle-market lending activities and institutional investors chased higher yields and bespoke contractual protections that public markets rarely provide. Depending on the metric used, the asset class was measured at roughly three trillion dollars at the start of 2025, and broader aggregates that count new direct-lending and alternative-credit strategies put total activity higher by late 2025. The expansion created a patchwork of fund structures—closed-end funds, evergreen vehicles, BDCs and specialty credit arms—whose differing liquidity mechanics and reporting cadences now determine how quickly pricing moves flow through to investor outcomes.

How AI became a credit stress test

The immediate trigger for market reappraisal was a swift re-rating of public software equities as market participants and analysts debated which product categories would be augmented by AI and which would be commoditized or displaced by AI-native competitors. When public multiples fall sharply, the comparables and exit assumptions that underpin private valuations and loan covenants are called into question, and loans underwritten on the basis of durable subscription economics are exposed to model risk. For private borrowers that relied on predictable renewal streams and long sales cycles, the speed of adoption of new generative or automation tooling can shorten expected monetization windows and compress forward revenue forecasts in ways that were not fully priced at origination.

For lenders, the conversion of lower revenue expectations into actual credit losses follows several channels: covenant breaches that permit lenders to accelerate testing or seek remedial action, an uptick in amendments and waivers that dilute contractual protection, and, in the worst case, default events where recovery values are driven by a narrow set of strategic acquirers. Software collateral is largely intangible and, in distress, recovering value typically depends on buyers who both understand the product and are willing to retain teams and customers; absent that buyer set, recoveries can be low relative to loans secured by tangible assets.

Concentrations, opacity and the role of BDCs

Exposure across the private credit universe is uneven and that unevenness matters for transmission of shocks. Publicly traded business development companies and listed credit arms attract outsized attention because their periodic disclosures make concentrations and valuation marks visible to outside investors, whereas many closed-end funds report less frequently and provide less granular loan-level data. Some managers report modest single-digit software allocations, while other vehicles and vintages show much higher effective concentration once loan seasoning, sponsor support and vintage effects are taken into account; those distinctions materially change loss prospects at the fund level.

Liquidity mechanics amplify valuation uncertainty because different fund structures respond differently to investor flows and market signals. Closed-end funds with contractual lock-ups and staged holdings have operational tools to manage through temporary dislocations, while evergreen funds and BDCs that distribute quarterly income and face periodic redemptions can be forced into tactical decisions when sentiment shifts. Public-market discounts to net asset value can widen quickly, creating pressure on managers to shore up capital, adjust distributions or revise portfolio marks, and each of those responses has knock-on effects for perceived solvency and investor confidence.

Measured risk and model uncertainty

The immediate response inside asset managers has been granular, loan-by-loan diligence that focuses on revenue composition, contract tenure, customer concentration and gross-margin durability. Underwriting committees are distinguishing firms with multi-year, mission-critical enterprise contracts and high switching costs from vendors with short-duration, low-switching-cost revenue that can be arbitraged by low-cost AI alternatives. That qualitative sorting is being supplemented with quantitative sensitivity testing that stresses exit multiples, buyer pool depth and time-to-recovery under alternative disruption timelines.

Model uncertainty is acute because recovery-rate assumptions for intangible-heavy collateral are highly path-dependent and sensitive to timing, financing availability and buyer appetite. Scenario analysis that layers technology-driven revenue shocks over macro and liquidity stress cases produces wide bands of potential default and loss outcomes; managers say these exercises are being used less as point forecasts and more as guides to covenant design, reserve sizing and workout playbooks. The output of such models will shape covenant setters, pricing spreads and the appetite for subordinated exposure in the months ahead.

Market reaction and strategic implications

The market response has so far been uneven but visible: several listed credit managers and BDCs registered share-price weakness as investors re-priced potential software concentrations, and trade commentary recorded meaningful mark-downs in public software indices that in turn amplified scrutiny of private exposures. Some managers pushed back publicly, stressing the seniority of their lien positions and the diversity of their books, while others accelerated investor communications and offered more granular portfolio disclosures to limit uncertainty. The result has been a near-term increase in liquidity-seeking behaviour among investors and a faster tempo of credit committee reviews.

Strategically, the episode may accelerate two durable shifts. First, lenders are likely to tighten covenant packages, demand larger equity cushions and prefer collateralized structures in sectors judged vulnerable to rapid AI-driven substitution. Second, capital allocation may bifurcate: strategies emphasizing tangible collateral, shorter hold periods and strong workout capabilities may attract incremental allocations, while deeply subordinated or covenant-lite exposures will be repriced or face tougher fundraising conditions. Over time, managers that can demonstrate operational monitoring, active workout experience and transparent valuation processes should see relative investor advantages.

What investors should watch next

Investors evaluating private credit exposure should insist on loan-level schedules that differentiate software sub-sectors and reveal revenue durability metrics such as contract length, churn and customer concentration by cohort. Review covenant amendment histories, the incidence of waivers, and any equity cures or sponsor support that has been deployed; evaluate the redemption mechanics and liquidity profiles of vehicles that hold meaningful credit risk; and monitor secondary-market pricing for listed credit wrappers as an early signal of sentiment stress. Also track any forbearance announcements or distressed exchanges, since these operational outcomes determine realized recoveries far more than headline NAV movements.

The episode is a reminder that private markets deliver yield at the cost of illiquidity and information asymmetry, qualities that matter most when structural change accelerates. Whether the current repricing proves a contained correction or the leading edge of a broader impairment cycle will depend on the speed and breadth of AI-driven revenue disruption, underwriting discipline in the private-credit ecosystem, and the depth of strategic buyers for distressed software assets. For institutional investors, the prudent response is disciplined, granular scrutiny, closer engagement with managers, and contingency planning for stressed scenarios; monitoring covenant triggers, peer secondary pricing and supervisory commentary will help convert uncertainty into actionable risk budgets.

Written by Nick Ravenshade for NENC Media Group, original article and analysis.

Sources: Reuters, Bloomberg, Morgan Stanley, AIMA.