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.”
………………………………………………………………………………………………………………………………………………………………………………………………
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.
…………………………………………………………………………………………………………………………………………………………………………………………………
Data Center Compute Server & Storage Room; iStock Photo credit: Andrey Semenov
……………………………………………………………………………………………………………………………………………….
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!
………………………………………………………………………………………………………………………………………………………………………………
References:
https://www.wsj.com/tech/ai/debt-is-fueling-the-next-wave-of-the-ai-boom-278d0e04
5 thoughts on “Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?”
Leave a Reply to Anonymous Cancel Reply
Most of the best-performing stocks in the S&P 500 this year are directly tied to the AI boom. Data storage companies Seagate Technology (STX) and Western Digital (WDC) have seen their shares nearly triple in value this year, while Palantir (PLTR) and Applovin (APP), two software firms that have excelled at translating AI capabilities into revenue, have more than doubled. And despite a rough start to 2025, all of the Magnificent Seven stocks are up since the start of the year.
Massive infrastructure investment from the likes of Microsoft (MSFT), Alphabet (GOOG), Amazon (AMZN) and Meta (META) has been a primary source of fuel for the AI rally. Their spending has caused revenue at chipmakers like Nvidia (NVDA), Broadcom (AVGO) and Micron (MU) to explode, and underpinned the narrative that AI demand is insatiable.
https://finance.yahoo.com/news/ai-stocks-fueled-bull-market-194514237.html
Neoclouds are emerging as a distinct category of cloud providers built specifically for AI. Their core attributes include GPU-as-a-service models, ultra-low-latency networking, and software stacks optimised for large-scale AI workloads. Unlike traditional infrastructure-as-a-service or platform-as-a-service offerings, neoclouds provide capabilities tailored to AI, from training and inference to fine-tuning and full model hosting.
Global and European players are already establishing themselves in this space, bringing new competition to hyperscalers and regional providers. For the wider ecosystem, the implications are clear. Neoclouds introduce new types of tenants, push facilities toward higher-density requirements, and require earlier supplier engagement than conventional cloud builds.
According to Kristina Lesnjak, EMEA Research Manager, “AI is rapidly reshaping the foundations of cloud infrastructure, driving demand for GPU scale and ultra-low latency that neoclouds are uniquely positioned to deliver. With record levels of investment flowing into the UK’s digital infrastructure and leading technology firms aligning around AI, the momentum behind this transformation has never been stronger.”
https://www.dcbyte.com/news-blogs/ai-neocloud-uk-infrastructure/
From a San Jose Mercury news article titled,
Chatbot dreams generate AI nightmares for Bay Area lawyers
A Palo Alto lawyer with nearly a half-century of experience admitted to an Oakland federal judge this summer that legal cases he referenced in an important court filing didn’t actually exist and appeared to be products of artificial intelligence “hallucinations.”
A specialist in computer law, Jack Russo found himself in the rapidly growing company of lawyers publicly shamed as wildly popular but error-prone artificial intelligence technology like ChatGPT collides with the rigid rules of legal procedure.
Hallucinations — when AI produces inaccurate or nonsensical information — have posed an ongoing problem in the generative AI that has birthed a Silicon Valley frenzy since San Francisco’s OpenAI released its ChatGPT bot in late 2022. In the legal arena, AI-generated errors are drawing heightened scrutiny as lawyers flock to the technology, and irate judges are making referrals to disciplinary authorities and, in dozens of U.S. cases since 2023, levying financial penalties of up to $31,000, including a California-record fine of $10,000 last month in a Southern California case.
Since 2024, private investors have spent $259B funding AI start-ups, according to Crunchbase. OpenAI is making an early bid to become a colossus in the AI age, but many of these new companies may not yet be on anyone’s radar, and some might not even exist. There are long-term risk tied to OpenAI, which underlies Oracle’s growth.
There’s still no clear answer as to where OpenAI will get the money for its Oracle cloud contract. Or how Oracle itself will finance the capital expenditures required to fulfill its end of the bargain. Perhaps most complicated: Where will the companies find the electricity to power these data centers?
Oracle’s long-term value relies on answers to these thorny questions.
https://www.barrons.com/articles/nobel-prize-ai-innovation-disruption-7cd620ce
From Nov 8, 2025 NY Times:
According to an investor offering sheet obtained by DealBook, Blackstone is on the cusp of closing a $3.46 billion commercial-mortgage-backed securities (C.M.B.S.) offering to refinance debt held by QTS, the biggest player in the artificial intelligence infrastructure market. It would be the largest deal of its type this year in a fast-accelerating market. (Blackstone declined to comment.)
The bonds would be backed by 10 data centers in six markets (including Atlanta, Dallas and Norfolk, Va.) that together consume enough energy to power Burlington, Vt., for half a decade.
Blackstone’s offering is part of the latest push in the A.I. infrastructure financing blitz. According to McKinsey, $7 trillion in data center investment will be required by 2030 to keep up with projected demand. Google, Meta, Microsoft and Amazon have together spent $112 billion on capital expenditures in the past three months alone.
The sheer scale of spending is spooking investors: Meta’s stock tumbled 11 percent after the company revealed its aggressive capital expenditure plans last week, and tech stocks have sold off this week on overvaluation fears.
Now, the tech giants are turning to financing maneuvers that may add to the risk. To obtain the capital they need, hyperscalers have leveraged a growing list of complex debt-financing options, including corporate debt, securitization markets, private financing and off-balance-sheet vehicles. That shift is fueling speculation that A.I. investments are turning into a game of musical chairs whose financial instruments are reminiscent of the 2008 financial crisis.
Big tech companies are looking for new sources of financing. While Meta, Microsoft, Amazon and Google previously relied on their own cash flow to invest in data centers, more recently they’ve turned to loans. To diversify their debt, they’re repackaging much of it as asset-backed securities (A.B.S.). About $13.3 billion in A.B.S. backed by data centers has been issued across 27 transactions this year, a 55 percent increase over 2024.
If investors want to buy data center A.B.S., they have two options, according to Sarah McDonald, a senior vice president in the capital solutions group at Goldman Sachs: They can invest in a data center that has one tenant, like a hyperscaler, or in a co-location data center, which has thousands of smaller tenants. The former is an investment-grade tenant with a long-term lease, but the risk is highly concentrated; the latter is most likely renting out to noninvestment-grade tenants with short-term leases, but the investment is extremely diversified.
Digital infrastructure “is something that investors have a huge appetite for,” McDonald said.
Despite the increase in popularity, data center securities are just a small slice of the A.B.S. market, which is dominated by credit card, auto, consumer and student loans.
Blackstone’s $3.46 billion C.M.B.S. offering may seem like small potatoes compared with some other debt-fueled deals, such as Meta’s $30 billion corporate offering to finance its data center in Louisiana. But it’s unprecedented for the C.M.B.S. market, where issuance for data-center-backed deals was just $3 billion for all of 2024.
“They realize how much cash they’re going to need, so they’re getting the C.M.B.S. market comfortable with this type of asset,” said Dan McNamara, the founder and chief investment officer of Polpo Capital, a hedge fund that focuses on C.M.B.S. He added that while most traders in the market were well versed in assets like office space or industrial buildings, with data centers, “it’s not traditional ‘bricks and sticks’ commercial real estate.”
To complicate matters further, the share of single-asset-single-borrower securities (S.A.S.B.) — for example, the assets inside the bond being sold are all from the same company or a single data center — is rising, with 13 percent of all S.A.S.B. deals coming from data centers, according to Goldman Sachs.
“It’s one company, and these assets are quite similar. If there’s a problem with A.I. data centers, like if their current chips are obsolete in five years, you could have big losses in these deals,” McNamara said. “That’s the knock on S.A.S.B.: When things go bad, they go really bad.”
https://www.nytimes.com/2025/11/08/business/dealbook/debt-has-entered-the-ai-boom.html