AI companies are looking to spend trillions of dollars on data centers to power their increasingly resource-intensive AI models — an astronomical amount of money that could threaten the entire economy if the bet doesn’t pay off.
As the race to spend as much money as possible on AI infrastructure rages on, companies have become increasingly desperate to keep the cash flowing. Firms like OpenAI, Anthropic, and Oracle are exhausting existing debt markets — including junk debt, private credit, and asset-backed loans — in increasingly desperate moves, as Bloomberg reports, that are raising concerns among investors.
“The numbers are like nothing any of us who have been in this business for 25 years have seen,” Bank of America managing head of global credit Matt McQueen told Bloomberg. “You have to turn over all avenues to make this work.”
AI companies have accrued at least $200 billion in debt, per the publication. A more realistic figure is likely considerably higher, as that estimate doesn’t count undisclosed private deals.
Oracle announced over the weekend that it’s raising a staggering $45 billion to $50 billion in debt and equity sales to build additional cloud infrastructure capacity, plans that once again highlighted persistent concerns over a growing AI bubble. The company’s efforts to build out AI data centers have firmly pushed the company into a negative cash flow, leaving it on the hook for many billions of dollars in the coming years.
Elon Musk’s plans to merge his space company SpaceX with xAI ahead of a rumored blockbuster IPO are also raising eyebrows, suggesting the billionaire’s nascent AI startup is looking to secure even more funds for highly ambitious plans including sending data centers to space.
Despite the mounting capital expenditures, the industry still has a lot of work left to do to justify its heavy borrowing. Many AI companies have essentially given up on even pretending their short- or medium-term goal is to make money as they turn to measuring “ambition, not success,” as TechCrunch AI editor Russell Brandom explained in a recent piece.
The tech itself is also starting to show diminishing returns with each new model release. Even the most powerful AI models are still struggling with the very basics, while suffering from the same drawbacks, including persistent hallucinations, that have plagued them for years now.
Demand could also be drying up, making it even harder to justify all of that debt. Early data suggests that subscriber growth for online services, like OpenAI’s ChatGPT, could already be levelling off. Meanwhile, OpenAI has already turned to stuffing ads into its services in a desperate bid to stem the bleeding, a move that CEO Sam Altman called a “last resort” as recently as 2024.
The short-term prognosis is starting to look grim. A growing mountain of debt could add significantly to borrowing costs, making AI data centers an even more expensive endeavor for already cash-strapped AI companies.
At least for now, investors are still seeing dollar signs — though many are also fretting that it’s only a matter of time until the bubble pops.
“There’s a view that if you can build a data center, there’s so much demand for data centers that you just can’t lose — it’s like selling beer to sailors,” SLC Management co-head of private fixed income Andrew Kleeman told Bloomberg. “But anytime there’s truly innovative technology, there’s usually a massive overinvestment, and then there’s a correction.”
More on growing debt: Major AI Companies Aren’t Even Pretending to Make Money
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