Credit investors are pouring billions of dollars into artificial intelligence investments, just as industry executives and analysts are raising questions about whether the new technology is inflating another bubble.

JPMorgan Chase & Co. and Mitsubishi UFJ Financial Group are leading the sale of a more than $22 billion loan to support Vantage Data Centers’ plan to build a massive data-center campus, people with knowledge of the matter said this week. Meta Platforms Inc., the parent of Facebook, is getting $29 billion from Pacific Investment Management Co. and Blue Owl Capital Inc. for a massive data center in rural Louisiana, Bloomberg reported this month. 

And plenty more of these deals are coming. OpenAI alone estimates it will need trillions of dollars over time to spend on the infrastructure required to develop and run artificial intelligence services. 

At the same time, key players in the industry acknowledge there is probably pain ahead for AI investors. OpenAI Chief Executive Officer Sam Altman said this week that he sees parallels between the current investment frenzy in artificial intelligence and the dot-com bubble in the late 1990s. When discussing startup valuations he said, “someone’s gonna get burned there.” And a Massachusetts Institute of Technology initiative released a report indicating that 95% of generative AI projects in the corporate world have failed to yield any profit. 

Altogether, it’s enough to make credit watchers nervous.

“It’s natural for credit investors to think back to the early 2000s when telecom companies arguably overbuilt and over borrowed and we saw some significant writedowns on those assets,” said Daniel Sorid, head of U.S. investment grade credit strategy at Citigroup. “So, the AI boom certainly raises questions in the medium term around sustainability.”

The early build-out of the infrastructure needed to train and power the most advanced AI models was largely funded by the AI companies themselves, including tech giants like Alphabet Inc.’s Google and Meta Platforms Inc. Recently, though, the money has been increasingly coming from bond investors and private credit lenders.

The exposure here comes in many shapes and sizes, with varying degrees of risk. Many large tech companies — the so-called AI hyperscalers — have been paying for new infrastructure with gold-plated corporate debt, which is likely safe due to the existing cash flows that secure the debt, according to recent analysis from Bloomberg Intelligence.

Much of the debt funding now is coming from private credit markets.  

“Private credit funding of artificial intelligence is running at around $50 billion a quarter, at the low end, for the past three quarters. Even without factoring in the mega deals from Meta and Vantage, they are already providing two to three times what the public markets are providing,” said Matthew Mish, head of credit strategy at UBS. 

And many new computing hubs are being funded through commercial mortgage-backed securities, tied not to a corporate entity, but to the payments generated by the complexes. The amount of CMBS backed by AI infrastructure is already up 30%, to $15.6 billion, from the full year total in 2024, JPMorgan Chase & Co. estimated this month.

Sorid and a colleague at Citi put out a report on Aug. 8 focusing on the particular risks for the utility firms that have boosted borrowing to build the electrical infrastructure needed to feed the power-hungry data centers. They and other analysts share a commonly held concern about spending so much money right now, before AI projects have shown their ability to generate revenue over the long term. 

“Data center deals are 20 to 30 year tenor fundings for a technology that we don’t even know what they will look like in five years,” said Ruth Yang, global head of private market analytics at S&P Global Ratings. “We are conservative in our assessment of forward cash flows because we don’t know what they will look like, there’s no historical basis.”

The stress has begun to appear in the rise of payment-in-kind loans to tech-oriented private credit lenders, UBS Group noted. In the second quarter, PIK income in BDCs reached the highest level since 2020, climbing to 6%, according to UBS.

But the fire hose of money is unlikely to stop anytime soon. 

“Direct lenders are constantly raising capital, and it has to go somewhere,” said John Medina, senior vice president in Moody’s Global Project and Infrastructure Finance Team. “They see these hyperscalers, with this massive capital need, as the next long-term infrastructure asset.” 

This story was originally featured on Fortune.com

​“Private credit funding of artificial intelligence is running at around $50 billion a quarter, at the low end, for the past three quarters."