Construction, Power Availability and Tenant Concentration: A BIS Bulletin on Financing the AI Boom

The Bank for International Settlements published BIS Bulletin No 120 on January 7, 2026, under the title "Financing the AI boom: from cash flows to debt." Among its key takeaways, it says that "The size of anticipated investment needs will require firms to shift the source of financing from operating cash flows to debt, with private credit playing a rapidly increasing role." Among the risks it says may push that financing beyond banks and bonds, it names power availability. The views in it, the bulletin says, "are those of the authors and do not necessarily reflect the views of the BIS or its member central banks." Parts of it follow, not the whole.

From Cash Flows to Debt

The firms driving the AI investment boom, the bulletin says, "have historically operated with substantially less debt than other firms," relying on highly profitable operations to fund their investments. They have since ramped up their capital expenditures significantly, both in absolute terms and as a share of revenues. "Indeed, free cash flows have recently lagged capital expenditures in absolute amounts." Equity, it says, "may in turn be neither timely nor cost-effective at the current juncture," because AI valuations are volatile and concentrated, issuance windows are narrow, and new stock sales can be costly and dilutive for long-dated, asset-heavy projects.

Debt, through corporate bonds, leasing arrangements or loans, "allows investors to spread costs over time and align financing maturities with the long economic life of data centre assets." "Specific risks concerning construction, power availability and tenant concentration, however, mean that financing may fall outside the scope of traditional bank and bond financing (notwithstanding reportedly record bond issuance)."

Private credit, the bulletin says, typically means non-bank credit from funds, mostly to small or medium-sized non-financial firms. Lenders negotiate the deals directly with borrowers and hold the loans on their balance sheets until maturity. Its ability to provide bespoke financing that accommodates construction and operational risks, the bulletin says, "arguably make private credit well placed to fund large, asset-heavy AI projects."

Power availability sits on the bulletin's list beside construction and tenant concentration. For a lender, the plain question is whether the power has been settled in writing before the money goes in.

What the Funds Have Lent

Lending by private credit funds to AI-related sectors has grown fast. Outstanding loan amounts have increased from near zero to over $200 billion as of the bulletin's date, and the share of private credit loans to AI-related companies from less than 1% of total outstanding loan volumes to almost 8%. A note under the graph of these loans defines AI firms there as firms in three verticals defined by a data provider: artificial intelligence, big data and cloud tech. Extrapolating from projected AI investment growth of 50–300%, the authors estimate that outstanding private credit to AI firms "could reach around $300–600 billion by 2030."

The terms of these loans, the bulletin says, "do not differ markedly from those to companies in other sectors." "Loans to AI-related companies are just as likely to be secured as those to other sectors (46% vs 48%) but are on average substantially larger ($169 million vs $90 million, Graph 3.B)." Maturity and rate spreads are similar too, at 4.7 against 4.8 years and 6.2 against 6.1 percentage points over a benchmark rate.

For the funds, exposure "remains modest for the average private credit fund." About 20% of all private credit funds lend to AI-related sectors, up from 5% in 2010. "However, for the average fund, loans to AI-related firms still account for only about 5% of total volumes, up from close to 0% in 2010."

Spreads and Valuations

"The increasing reliance on debt introduces vulnerabilities to the broader financial system." AI firms, the bulletin says, "now face higher leverage, which could amplify shocks and affect the health of financial intermediaries" if AI spending does not pay off as expected, and some financing structures "might mask leverage by moving it off the balance sheet." "Yet leverage does not disappear by being out of sight." Market commentary, it adds, points to investor concerns "about the long-term value of collateral (eg data centres) underpinning some large-scale deals."

The loan spreads charged on private credit loans to AI firms "are close to those charged to non-AI firms," and a footnote says the difference stays insignificant after accounting for loan terms and borrower characteristics. "If loan spreads reflect the risk of the underlying investment, this pattern suggests that lenders judge AI-related loans to be as risky as the average loan to any private credit borrower." That, it says, "stands in stark contrast to the high equity valuations of AI companies." "This schism suggests that either lenders may be underestimating the risks of AI investments (just as their exposures are growing significantly) or equity markets may be overestimating the future cash flows AI could generate."

A spread close to any other borrower's shows no separate charge for power that arrives late. Whether that risk is priced elsewhere in these deals, the bulletin does not show.

"Overall," it says, "while AI may deliver a sustained boost to economic growth, it remains to be seen whether this potential will be realised."