Debt-hungry AI companies face increased risk as bond yields spike

Spools of electrical wires outside a series of assembly tents during a media tour of the Stargate AI data center in Abilene, Texas, US, on Tuesday, Sept. 23, 2025. Stargate is a collaboration of OpenAI, Oracle and SoftBank, with promotional support from President Donald Trump, to build data centers and other infrastructure for artificial intelligence throughout the US.

Kyle Grillot | Bloomberg | Getty Images

With Treasury yields climbing this week to their highest levels since 2007, companies reliant on debt are poised to see their borrowing costs rise. That means the AI infrastructure buildout, which has already reached historic levels, is about to get even more expensive.

JPMorgan Chase estimated in June that $4.1 trillion in AI-related debt will be issued through 2030, as data center companies and others tied to the artificial intelligence boom race to build up capacity to meet what many industry experts view as insatiable demand for AI services.

As borrowers go back to the market, they're now looking at a 10-year Treasury yield that sits near 5.17%, up about 1 percentage point since the start of the year, meaning companies issuing debt are going to have to offer more attractive rates of return to lure investors.

The market isn't in panic mode, at least not yet. Shares of debt-heavy neocloud CoreWeave have held up fine, rising almost 8% this week, while Oracle, which has counted on the debt market for its AI expansion, has had a tougher time, falling 7% for the week and about 30% this year.

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CoreWeave vs. Oracle this week

Meanwhile, Japan's SoftBank, a principal provider of capital for AI projects, raised $11.1 billion in a junk-bond sale this week, with yields as high as 9.75% for the 7-year tranche.

Warning signs?

A senior private credit investor, who asked to remain unnamed in order to speak candidly on the matter, told CNBC that, moving forward, neocloud deals will be more difficult to finance, because the companies have less cushion to absorb the costs.

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