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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchCircular AI deals are overlapping investment and commercial relationships: one company may invest in an AI firm that then buys computing capacity, chips, cloud services or infrastructure from that investor or a connected company. These links can help secure scarce inputs and coordinate expansion, but they can also make it harder to tell how much demand is backed by independent customers—and how much depends on financing or commitments within the same network. Regulators and international institutions identify risks to watch, not proof that a crisis is inevitable or that every linked deal is unsound.
What counts as a circular AI deal?
The phrase “circular financing” describes a pattern of overlapping investment, financing and commercial links—not a single standardized transaction. For example, a company invests in an AI developer; that developer uses some of the funding to buy compute from the investor or a related provider; and the provider relies on continued AI demand to justify building more capacity.
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The connection matters because the investment and the purchase contract can reinforce each other. The investment gives the buyer resources to expand, while the contract helps support the supplier’s expected revenue. That may be a practical way to obtain critical inputs or coordinate infrastructure. It does not, by itself, establish misconduct, artificial demand or a loss.
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The Bank for International Settlements (BIS) distinguishes investment relationships from commercial supply-chain ties. A supplier contract is not automatically circular financing; the relevant question is whether it overlaps with investment, lending, guarantees or other commitments in a way that links counterparties’ fortunes.
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What the BIS figures show—and what they do not
BIS Bulletin 137, published on 1 October 2026, examines AI-firm investment deals from 2021 through 2025. Its figures describe that dataset and its definitions; they are not estimates of the share of all AI revenue or of all AI investment worldwide.
| Measure | BIS finding for 2021–2025 | How to read it |
|---|---|---|
| Investment deals by value targeting another AI firm | 28.7% | Share of AI firms’ investment deals, measured by deal value, in which an AI firm was the target. |
| Incoming investment in AI firms from other AI firms | 55.2% | Share of incoming investment in AI firms that came from other AI firms. |
| AI-to-AI investment deals with a commercial supply-chain relationship | 16.1% by deal count; 46.4% by deal value | Share of AI-to-AI investment deals that also involved a commercial supply-chain relationship between investor and target. Count and value produce different shares. |
The last row is especially important: a minority of the deals by count represented a larger share by value. None of these statistics means that all the relationships were circular, improper or dependent on one another. BIS says such ties can reflect the need to secure critical inputs and information asymmetries, while also increasing opacity and potential macroeconomic risk.
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The bulletin’s authors summarize the tension this way: “Circular investment relationships reflect key economic features such as the need to secure critical inputs and the presence of information asymmetries, yet they entail macroeconomic risks and increase opacity.” The statement is from the authors of BIS Bulletin 137; the publication notes that its views do not necessarily represent the BIS or its member central banks.
How connected deals can transmit a shock
Demand and earnings fall short
AI investment rests partly on expectations that adoption will generate future revenue and productivity gains. BIS Bulletin 130, published on 28 July 2026, says those gains remain uncertain and uneven across sectors and countries. If customers spend less than expected or returns arrive later, an AI company may cut expansion plans. That can reduce revenue for cloud, chip and infrastructure providers, weakening the assumptions behind their own investment and financing.
Debt turns a slowdown into a repayment problem
Large infrastructure projects require substantial spending before the associated revenue is certain. Borrowing can shift exposure from technology companies’ cash balances toward banks, bondholders, private-credit funds and other lenders. If demand or earnings disappoint, debt payments remain due and refinancing may become harder.
BIS Bulletin 120, published on 7 January 2026, said anticipated investment needs would push firms to rely more on debt as well as operating cash flow, with private credit playing a rapidly increasing role. It described macrofinancial risks as moderate at that time and said sustainability depended on firms meeting high earnings expectations. The IMF’s April 2026 Global Financial Stability Report also described AI-related capital spending supported by bonds, leveraged loans and intercorporate arrangements, sometimes forming circular financing structures. It warned that cash buffers and earnings might not be enough to meet future spending, potentially pressuring balance sheets.
Concentrated exposures move together
If a small number of central firms, lenders or infrastructure providers connect many participants, a change in one company’s outlook can affect several counterparties at once. Investors may also hold related exposures across public and private equity and debt markets. The European Central Bank’s (ECB) May 2026 Financial Stability Review highlighted concentrated positions and the risk of correlated repricing as concerns; its cited section used data through 19 May 2026.
The ECB also reported a historical association: 15% of years with particularly strong growth in both equity prices and business debt were followed by a financial crisis within two years. This is a finding about historical episodes, not an AI-specific forecast. At the time of the review, the ECB said business-debt growth remained low in the United States and euro area. The statistic is a reason to monitor the combination of rising equity prices and debt—not evidence that AI investment had caused a crisis.
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Complex commitments obscure who bears the loss
Investment, purchase agreements and infrastructure financing can be difficult to map across counterparties. An announced commitment is not necessarily funded capital, and it should not be treated as a recognized liability unless its terms and accounting treatment support that conclusion. Future-dated, conditional arrangements may expose participants differently from cash already invested or unconditional contractual obligations. The IMF and BIS both identify opacity and interconnections as concerns.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why firms make these arrangements
Linked investment and supply relationships can be commercially rational. A company may invest to help a supplier expand capacity that it needs, or an AI firm may secure access to compute in a market where critical inputs are constrained. An investor may also have better information about a business than an outside financier, while the target may need capital to build before it can serve customers.
The same arrangement can nevertheless blur the source of demand. If a provider’s growth case relies heavily on purchases from companies it has funded, those purchases may not offer the same evidence of independent end-customer demand as sales to unrelated customers. That is a question for examining a specific contract, not a conclusion that follows automatically from a relationship.
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How to assess a particular deal
Do not label two arrangements equivalent just because both involve an AI company and an infrastructure provider. Map the cash, obligations and counterparties first:
- Identify each connection. Is it equity investment, a loan, a guarantee, a purchase commitment or several of these? Record which entity is the investor, borrower, supplier and customer.
- Check revenue dependence. Is the investor also a supplier or customer? What share of the target’s expected revenue depends on that relationship, and how much comes from unrelated customers?
- Trace the funding source. Is the spending funded by operating cash, equity, bonds, bank lending or private credit? Debt and equity place risk on different parties.
- Separate what is committed from what is funded. Check whether a commitment is conditional, future-dated or already funded, and whether the agreement creates an unconditional obligation.
- Look for concentration. How much exposure sits with a single counterparty, lender, supplier or group of connected firms? Could several positions be affected by the same demand or financing shock?
- Check the scope of the evidence. Note the source’s date, geography, sample and definition. A deal-count share, a deal-value share and a national debt-growth measure answer different questions.
Could the AI boom cause a financial crisis?
It is possible for a sharp reversal in demand, earnings or valuations to spread through connected firms and lenders, particularly if debt and concentrated exposures have grown. But the official assessments cited here describe channels and vulnerabilities, not a prediction that a crisis will occur. BIS assessed macrofinancial risks as moderate in January 2026, while the ECB’s May review said US and euro-area business-debt growth remained low. The key uncertainty is whether expected earnings and productivity gains will support the scale of investment and financial obligations being built around them.
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