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Private Credit Investors Pull Capital as AI Risk in Software Portfolios Goes Unmeasured

The private credit asset class built its reputation on stability—consistent yields, low volatility, long lock-ups that insulated managers from the redemption cycles that plagued public fund structures. That reputation is now under pressure from a specific and poorly disclosed risk: exposure to mid-market software borrowers whose revenue models are being tested by AI adoption at the enterprise level.

Capital Flows Through an Opaque Chain

The current exposure traces to decisions made over seven years. PE firms acquired life-insurance and annuity businesses, gaining access to policyholder reserves—a stable, long-duration capital base. Those reserves were channeled into proprietary private credit funds that operated with infrequent marks and minimal asset-level disclosure. The credit funds deployed capital into PE-owned portfolio companies, with a significant concentration in mid-market software businesses during the 2022–2024 period.

Eileen Appelbaum of the Center for Economic and Policy Research documented this chain in an April 2026 analysis, focusing specifically on the disclosure gaps and the insulation the structure creates between ultimate capital providers and the assets backing their commitments. The analysis landed at a moment when the LP base was already filing elevated redemption requests.

Why AI Displacement Is Specifically Disruptive to These Portfolios

Credit underwriting for software companies in 2022 and 2023 assumed that enterprise software revenues would continue compounding at the rates that had defined the prior decade. That assumption did not model a scenario where generative AI tools allowed enterprise buyers to build or replace software functionality at substantially lower cost.

The disruption is not uniform. Infrastructure software—databases, security, cloud operations—remains largely insulated because AI does not yet substitute for the underlying plumbing of enterprise computing. Vertical SaaS with deep workflow integration and regulatory dependencies is more defensible than the category-level headline suggests. The exposure that matters sits in horizontal application software: tools that cover productivity, document management, CRM, and project management at a layer where AI substitution is already technically feasible and increasingly cost-effective.

The Disclosure Gap That Drives Exits

Fund letters do not tell LPs how much of their allocation sits in horizontal application versus infrastructure software. AI-displacement-risk metrics do not appear in any standard disclosure format at any major private credit fund. When the risk category is real but unquantifiable from the outside, LPs who want to manage their exposure have one available tool: file a redemption request.

Two perpetual private credit vehicles moved to cap quarterly withdrawals in March 2026. A third followed in April. None of the three disclosed material credit losses alongside the gate announcements. The secondary market for fund interests has moved the discount to reflect anticipated future marks—pricing the probability of losses, not their confirmation.

Structural Arguments and Their Limits

Private credit managers emphasize the structural features that distinguish their loan books from public high-yield: negotiated covenants, private workout processes, absence of forced-sale mechanics. These features are real and relevant. They are also arguments about process rather than outcome—they describe how the stress would be managed, not what the stress will cost.

The question LPs are asking is not procedural. It is economic: at what level of software-borrower revenue decline does the NAV move materially? That question requires loan-level data that the funds do not currently provide. Until disclosure practices change—an outcome that historically follows LP pressure rather than preceding it—the redemption queue is the clearest signal available about how the LP community is answering it.

NAV prints from the largest perpetual vehicles over the second and third quarters of 2026 will be the first hard data. The pace at which AI-displacement metrics begin appearing in LP letters will indicate whether the LP community is pressuring managers forcefully enough to produce disclosure reform within this cycle.

Source: Private Credit Fund Redemptions Climb Sharply, Some Caps Now in Place

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