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Measuring risk in the AI financing boom

A shift towards debt raises the potential fallout from the data centre spending spree

The artificial intelligence boom is entering a new and riskier phase. Global capital expenditure on chips, data centres and cloud infrastructure has, so far, been driven by hyperscalers, funded largely through their vast internal cash balances. But the projected scale of computing power needed for generative AI is now prompting a shift towards more leveraged, opaque and circular financing structures, which raises the economic stakes riding on the technology’s success.

Between now and 2029, global spending on data centres is forecast to hit almost $3tn, according to Morgan Stanley. Big Tech groups will remain major spenders, but cash flows from their advertising and cloud computing businesses can only stretch so far. Many are increasingly looking to public and private credit sources to support further expansion. In August, Meta raised $29bn — including $26bn of debt — from private capital investors to fund centres in Ohio and Louisiana.

Although large tech groups still enjoy strong credit ratings, debt is being channelled into projects for non-investment-grade borrowers, such as CoreWeave, ChatGPT developer OpenAI and smaller AI start-ups. Finance is also being secured from other companies within the tech supply chain, creating a dense and interdependent web of exposures. This year OpenAI has announced over $1tn worth of deals for computing power with Nvidia, Oracle, CoreWeave, AMD, and, on Monday, Broadcom. Some agreements have involved complex circular financing arrangements.

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