Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?
IEEE Techblog has called attention to the many challenges and risks inherent in the current mega-spending boom for AI infrastructure (building data centers, obtaining power/electricity, cooling, maintenance, fiber optic networking, etc) . In particular, these two recent blog posts:
AI Data Center Boom Carries Huge Default and Demand Risks and
This article focuses on the tremendous debt that Open AI, Oracle and newer AI cloud companies will have to obtain and the huge hurdles they face to pay back the money being spent to build out their AI infrastructures. While the major hyperscalers (Amazon, Microsoft, Google and Meta) are in good financial shape and won’t need to take on much debt, a new wave of heavily leveraged firms is emerging—one that could reshape the current AI boom.
OpenAI, for example, is set to take borrowing and large-scale contracts to an unbelievable new level. OpenAI is planning a vast network of data centers expected to cost at least $1 trillion over the coming years. As part of this effort, the company signed a $300 billion, five-year contract this month under which Oracle “is to set up AI computing infrastructure and lease it to OpenAI.” In other words, OpenAI agreed to pay Oracle $300 billion over five years for the latter company to build out new AI data centers. Where will OpenAI get that money? It will be be burning billions in cash and won’t be profitable till 2029 at the earliest.
To fulfill its side of the deal, Oracle will need to invest heavily in infrastructure before receiving full payment—requiring significant borrowing. According to a recent note from KeyBanc Capital Markets, Oracle may need to borrow $25 billion annually over the next four years. This comes at a time when Oracle is already carrying substantial debt and is highly leveraged. As of the end of August, the company had around $82 billion in long-term debt, with a debt-to-equity ratio of roughly 450%. By comparison, Alphabet—the parent company of Google—reported a ratio of 11.5%, while Microsoft’s stood at about 33%.
Companies like Oracle and other less-capitalized AI players such as CoreWeave have little choice but to take on more debt if they want to compete at the highest level. Nebius Group, another Nasdaq-listed AI cloud provider similar to CoreWeave, struck a $19.4 billion deal in September to provide AI computing services to Microsoft. The company announced it would finance the necessary capital expenditures “through a combination of its cash flow and debt secured against the contract.”
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Sidebar – Stock market investors seem to love debt and risk:
CoreWeave’s shares have more than tripled since its IPO in March, while Nebius stock jumped nearly 50% after announcing its deal with Microsoft. Not to be outdone, Oracle’s stock surged 40% in a single day after the company disclosed a major boost in projected revenue from OpenAI in its infrastructure deal—even though the initiative will require years of heavy spending by Oracle.
–>What’s so amazing to this author is that OpenAI selected Oracle for the AI infrastructure it will use, even though the latter is NOT a major cloud service provider and is certainly not a hyperscaler. For Q1 2025, it held about 3% market share, placing it #5 among global cloud service providers.
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Data Center Compute Server & Storage Room; iStock Photo credit: Andrey Semenov
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Among other new AI Cloud players:
- CyrusOne secured nearly $12 billion in financing (much in debt) for AI / data center expansion. Around $7.9 billion of that is for new data center / AI digital infrastructure projects in the U.S.
- SoftBank / “Stargate” initiative: The Stargate project (OpenAI + Oracle + SoftBank + MGX, etc.) is being structured with major debt. The plan is huge—around $500 billion in AI infrastructure and supercomputers, and financing is expected to be ~70% debt, ~10% equity among the sources.
- xAI (Elon Musk’s AI firm): xAI raised $10 billion in combined debt + equity. Specifically ~$5 billion in secured notes / term loans (debt), with the remainder in equity. The money is intended to build out its AI infrastructure (e.g. GPU facilities / data centers).
There’s growing skepticism about whether these companies can meet their massive contract obligations and repay their debts. Multiple recent studies suggest AI adoption isn’t advancing as quickly as supporters claim. One study found that only 3% of consumers are paying for AI services. Forecasts projecting trillions of dollars in annual spending on AI data centers within a few years appear overly optimistic.
OpenAI’s position, despite the hype, seems very shaky. D.A. Davidson analyst Gil Luria estimates the company would need to generate over $300 billion in annual revenue by 2030 to justify the spending implied in its Oracle deal—a steep climb from its current run rate of about $12 billion. OpenAI has financial backing from SoftBank and Nvidia, with Nvidia pledging up to $100 billion, but even that may not be enough. “A vast majority of Oracle’s data center capacity is now promised to one customer, OpenAI, who itself does not have the capital to afford its many obligations,” Luria said.
Oracle could try to limit risk by pacing its spending with revenue received from OpenAI. Nonetheless, Moody’s flagged “significant” risks in a recent note, citing the huge costs of equipment, land, and electricity. “Whether these will be financed through traditional debt, leases or highly engineered financing vehicles, the overall growth in balance sheet obligations will also be extremely large,” Moody’s warned. In July (two months before the OpenAI deal), it gave Oracle a negative credit outlook.
There’s a real possibility that things go smoothly. Oracle may handle its contracts and debt well, as it has in the past. CoreWeave, Nebius, and others might even pioneer new financial models that help accelerate AI development.
It’s very likely that some of today’s massive AI infrastructure deals will be delayed, renegotiated, or reassigned if AI demand doesn’t grow as fast as AI spending. Legal experts say contracts could be transferred. For example, if OpenAI can’t make the promised, Oracle might lease the infrastructure to a more financially stable company, assuming the terms allow it.
Such a shift wouldn’t necessarily doom Oracle or its debt-heavy peers. But it would be a major test for an emerging financial model for AI—one that’s starting to look increasingly speculative. Yes, even bubbly!
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References:
https://www.wsj.com/tech/ai/debt-is-fueling-the-next-wave-of-the-ai-boom-278d0e04
