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Before investing, determine whether a fund’s AI exposure means lending to software companies that could face AI-driven competition, financing AI-related infrastructure such as data centers and power, or both. Then trace the underlying borrowers and cash flows, test their ability to repay, examine leverage and collateral, scrutinize loan valuations, and read the fund’s actual liquidity and fee terms. Sector-level data can help frame those questions, but it cannot tell you what an individual fund owns or whether it suits you.
What does “AI exposure” mean in a private credit fund?
It can describe two materially different credit risks. A fund may lend to a company whose business is exposed to AI-driven competition, or it may finance infrastructure and project cash flows associated with AI investment. A portfolio can have either exposure or both; the label alone does not tell you how borrowers will repay.
Software and SaaS borrowers: the business-disruption question
A software borrower may face competition from AI products, customers building alternatives themselves, or changing customer demand. The relevant question is not simply whether the company uses or sells AI. It is whether customers still need its product, keep paying for it, and generate enough cash flow for the borrower to service debt.
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The Bank for International Settlements (BIS), in a July 2026 bulletin, reported that business development companies (BDCs) had about $115 billion in loans to software firms—around one-fifth of BDC lending. In a separate measure of SaaS lending, BIS reported growth from almost $8 billion in 2015 to over $500 billion, or 19% of total direct loans, by the end of 2025; it also said a third of private credit funds had extended loans to SaaS firms. These are market-level figures, not measures of a particular fund’s exposure. BIS said uncertainty about generative-AI revenue had not yet affected the loans it examined; that observation does not establish that future disruption is absent.
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AI-related infrastructure: the project and payment-chain question
Other exposures may finance data centers, power, or related projects through direct loans, leases, guarantees, special-purpose vehicles (SPVs), asset-backed structures, or other financing. A project’s connection to AI does not by itself show whether the debt is well protected. Identify who is legally required to pay, what assets support the claim, whether the project is operational, and what conditions must be met for it to generate cash.
The Bank of England’s Financial Stability Report – July 2026 warns that bespoke and off-balance-sheet financing can make it harder to locate risk. It notes: “The riskiness of this debt depends on the underwriting terms, in particular the quality of the leases and guarantees which back debt holders’ claims.”
How much of the fund is exposed to AI or software?
Ask the manager for a current portfolio breakdown, with exposure shown by borrower, industry, geography, instrument, and financing structure. “AI exposure” should not be treated as a single bucket: ask the manager to distinguish software and SaaS borrowers from companies selling AI products, businesses vulnerable to AI substitution, and infrastructure connected to AI deployment.
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- Request each material position’s borrower or ultimate obligor, industry, geography, instrument, and share of the portfolio.
- Ask whether exposure figures are based on borrower revenue, the fund’s loan balances, collateral, or another definition; request the definitions and reporting date.
- Look through fund-of-funds interests, SPVs, co-lending arrangements, and asset-backed securities as far as the documents allow. If the manager cannot provide a look-through, establish what remains undisclosed.
- Check whether different positions rely on the same technology customers, counterparties, tenants, or project sponsors. Several loans may share one underlying source of risk.
BIS reports that several large BDCs share borrower pools, illustrating why concentration can arise across vehicles. That observation does not establish that every private fund has overlapping borrowers. Ask whether the manager’s own investments share borrowers or counterparties, and how it measures those concentrations.
Can the borrowers repay if assumptions change?
For software and SaaS loans
Assess the borrower’s ability to generate cash, rather than relying on a growth narrative or an AI-related label. Ask the manager to explain the borrower’s revenue model, customer retention, competitive position, and debt-service capacity, including the assumptions used in its base and downside cases.
- What portion of revenue is recurring, and how concentrated is it among customers?
- How easily can customers switch products or build alternatives? What evidence supports the manager’s view of switching costs and product differentiation?
- How have revenue and cash flow performed as AI tools and competing products have evolved?
- What are projected debt-service capacity and covenant headroom under the manager’s downside case?
- What refinancing assumptions are built into the repayment plan, and what happens if refinancing is delayed or unavailable?
For infrastructure and project-related loans
Establish whether the project is operational or still under construction, whether required power and capacity are available, and which parties are legally obligated to make payments. Review lease terms, guarantee quality, counterparty creditworthiness, construction and completion conditions, and refinancing needs. A planned project, a signed contract, and an operating asset are not interchangeable evidence of repayment capacity; ask what must happen before cash reaches the debt holder.
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Where does the risk sit in the financing structure?
Trace each material exposure from the fund through any intermediate vehicle to the borrower, project, collateral, and ultimate source of repayment. Identify fund-level borrowing as well as borrower- or asset-level borrowing. A loan’s stated borrower may not reveal which company, project, or counterparty ultimately bears the economic risk.
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How are the loans valued and portfolio changes reported?
Private loans are illiquid and are valued periodically, so a reported mark is not necessarily the price at which a position could be sold immediately. Ask who values the loans, how often, what methods and borrower information they use, how independent challenge works, and which events trigger a review.
- Ask how the manager updates marks after missed payments, covenant breaches, amendments, defaults, or material changes in a borrower’s business.
- Where relevant, compare reported marks with borrower results, public comparables, defaults or amendments, and observable transaction evidence.
- Ask how often investors receive portfolio updates and how quickly they are told about material developments.
- Review the valuation policy and determine whether the valuation process is independent of investment decisions or subject to a separate challenge.
BIS notes that BDC net asset values (NAVs) are largely determined by the book values of illiquid private loans. That market-level observation is a reason to understand a fund’s valuation process; it is not evidence that any specific manager has misstated values.
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First identify the legal vehicle: for example, a closed-end drawdown fund, publicly traded BDC, perpetual-life BDC, interval fund, or another structure. Then read the governing documents rather than relying on a general description such as “quarterly liquidity.” Check the lockup, redemption frequency, notice period, caps, gates, suspension rights, settlement timing, in-kind distributions, and manager discretion.
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Which fund documents and investor terms should you review?
Read the offering memorandum and the applicable limited partnership, shareholder, or other governing documents alongside the fee schedule, conflicts disclosures, valuation policy, and redemption provisions. Confirm how the vehicle is offered and which investor eligibility rules apply to you.
For US offerings relying on Regulation D, the Securities and Exchange Commission’s guidance says: “Self-certification by the investor alone (by checking a box) without the company having any other knowledge of the investor’s financial circumstances or sophistication is not sufficient to meet either the ‘reasonable belief’ standard or the ‘reasonable steps to verify’ requirement.” This guidance addresses US requirements; it does not settle the rules in other jurisdictions.
How should you compare funds you are actually considering?
Use current fund documents and comparable definitions, not an AI label or a headline return, to compare alternatives. A useful comparison includes:
- Strategy and type of AI exposure: software-business risk, infrastructure financing, or both.
- Borrower and counterparty concentration, including shared dependencies across positions.
- Borrower cash-flow resilience and the manager’s downside and refinancing assumptions.
- Debt seniority, collateral, covenants, structural subordination, and leverage at both borrower and fund level.
- For infrastructure positions, project status, contract and guarantee quality, and counterparty creditworthiness.
- Valuation methods, independent challenge, and investor reporting frequency.
- Fees, conflicts, legal structure, investor eligibility, and actual redemption rights.
Market analysis from BIS, the Bank of England, and the Federal Reserve provides context for questions to ask; it does not establish the holdings, fees, leverage, valuations, liquidity, or suitability of any unnamed fund. Those require review of the specific fund’s current documents and disclosures.
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