Artificial Intelligence (AI): Credit Boom Worries Economists

The cost of AI increasingly relies on borrowing. In a document titled << Building AI on credit: structures and spillovers >>, two economists from the Bank for International Settlements (BIS) analyze the financial arrangements that support AI infrastructures. Their finding: debt is rising, off-balance-sheet commitments complicate risk assessment, and connections between companies, funds, and banks are multiplying. For now, the observed repercussions on major bond markets remain limited.

Key points from this article:

• The Bank for International Settlements revealed that financing for artificial intelligence has increasingly relied on long-term borrowing and off-balance-sheet structures.

• Tech giants like Meta, Alphabet, and Oracle have raised colossal amounts in bond markets, altering the traditional financial balance.

Over $800 billion in investments expected by 2026

Alphabet, Amazon, Meta, Microsoft, and Oracle together plan over $800 billion in capital expenditures by 2026, according to the high forecasts from the companies included in the report. This amount represents about 2.5% of the US GDP.

To support this expansion, these five groups have issued $222 billion in bonds as of September 22, primarily with long maturities. Additionally, according to market sources cited, between $75 and $100 billion in bonds and asset-backed securities related to off-balance-sheet vehicles are included.

The Hyperion data center illustrates these arrangements. The joint venture involving Meta and funds managed by Blue Owl financed the project with $27.3 billion in private bonds. Meta does not consolidate this structure but supports its financing through lease commitments and limited protection of the residual value of the assets.

However, off-balance-sheet does not necessarily mean secret. The authors clarify that leases not yet commenced are subject to published information, without being counted as debt. The issue mainly lies in the difficulty of measuring total exposure.

Concentrated Risks, but Limited Bond Contagion

These structures indeed rely on the solidity of a small number of companies. An investor can thus hold simultaneously the bonds of a tech giant and those of several vehicles dependent on its rents, without fully measuring this concentration.

Banks also remain exposed: they sometimes finance the construction of data centers and lend to funds that buy their debt. At the same time, chips represent a fragile guarantee, as their value can decrease with new generations or simultaneous resales.

However, the report does not observe a general destabilization of the bond market. Over 18 days of announcements related to AI financing in 2026, the U.S. ten-year term premium increases by about 1.5 basis points. This effect fades in two sessions, and the yield spreads of well-rated corporate bonds do not change significantly.

Crypto: An Indirect Risk, Not a Conclusion of the Report

The authors emphasize that these are statistical associations, without proof of causality. A continuation of emissions at the same pace could nevertheless exert more lasting pressure on long-term rates.

Moreover, the report does not study Bitcoin or DeFi. For crypto investors, the connection is therefore an analysis: a sustained rise in long-term rates or losses among financial players could weigh on risk appetite.

However, it would be excessive to present each bond issuance as an equivalent deduction from the capital available for cryptocurrencies. The mechanism studied mainly concerns the price required to absorb more long-term debt.

The stakes thus go beyond just the IT bill: they concern the profitability of infrastructures, the concentration of commitments, and the identification of actors who bear potential losses. AI financing could therefore create turbulence in the coming months.

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