Two data center billionaires minted before anything is even built. A borrower seeking a loan for 150% of the construction cost. And companies that are using financial engineering to keep liabilities off their balance sheets.
For the skeptics, those are some of the examples of why the artificial intelligence data center boom is getting out of hand.
There’s a frenzy of development going on to support the AI revolution, and with it an insatiable demand for debt to fund it. Some estimate the overall infrastructure roll-out cost could reach $10 trillion, and with so many lenders lining up to throw cash at the assets, the fear is a bubble is building that could eventually leave equity and credit players facing substantial pain.
“One key risk to consider is the possibility that the boom in data center construction will result in a glut. Some data centers may be rendered uneconomic, and some owners may go bankrupt,” Oaktree Capital Management LP co-founder Howard Marks wrote in a note this week. “We’ll see which lenders maintain discipline in today’s heady environment.”
Given the flood of money going in, another danger is that there will be less credit available when facilities being constructed now using loans are in need of refinancing in three to five years’ time.
There’s also growing concern about the level of leverage, particularly given the technology may underperform its high expectations. In such a scenario, lenders may be even more reluctant to refinance, and companies would have to find additional equity or pay more to borrow.
“Momentum is strong, but if this is irrational exuberance, investors will lose when the music stops,” said Sadek Wahba, chairman and managing partner at infrastructure investor I Squared Capital. He said his firm is trying to be careful, cautioning that “every deal has nuance, and the fine print matters.”
The broader AI universe has also been caught up in the worries, with circular deals and soaring valuations taking a toll on the bullish sentiment that once dominated.
At Brookfield, Chief Executive Officer Bruce Flatt sees $5-$10 trillion of spending to finance the roll out of AI across everything from data centers to power infrastructure. McKinsey & Co. estimates almost $7 trillion is needed by 2030 just on data centers, including those for AI.
“These are sums that have never been invested before,” Flatt said.
OpenAI, for example, has plans to spend $1.4 trillion on AI infrastructure – and would spend more if it could. Chief Financial Officer Sarah Friar has repeatedly said that the company’s only constraint was finding more computing capacity.
If the scale of the deals is one worry, another surrounds how they are being packaged and structured.
Lenders are slicing and dicing debt and selling it on to other investors, meaning it becomes more and more opaque, according to Vinay Nair, chief executive officer at fintech platform TIFIN and a teacher in executive education programs at The Wharton School.
“You’re spreading this risk through the system,” he said. If there’s a decline, “I don’t think we totally understand all the ripple effects of this through that credit channel.”
Some borrowers have been shifting the risk from AI data centers off their balance sheets using the securitization markets, where the debt is tranched into slices with varying risks and returns and bought up by the likes of insurers and pension funds. A similar story is emerging in the graphics processing units that process the data.
With the lending environment so positive, some borrowers are even asking for more than 100% of the build cost for projects, according to two private credit lenders, who asked not to be identified as the details are private. In one case, the request was for 150%, with the property developer justifying the request on the basis of the uplift in valuation of the facility when rents start flowing, one of the people said.
Meanwhile, there’s also a risk of hype at play. Nuclear startup Fermi Inc. has yet to develop any data centers, but its valuation briefly jumped to more than $19 billion when it listed this year. That’s made billionaires of founders Toby Neugebauer and Griffin Perry, son of former US energy secretary Rick Perry.
But there’s also increasing market jitters about the borrowing and spending.
Fermi has slipped back below the level at which it went public. Concern about Facebook parent Meta Platforms Inc.’s spending hit its stock in late October and Oracle Corp.’s slumped this week after the company reported a jump in investment in data centers and other equipment.
Financing Plans
For years, landlords financed data centers with a combination of equity and debt and leased out the space. Hyperscalers, large cloud computing providers like Microsoft Corp. and Alphabet Inc.’s Google, also developed sites themselves as cloud services took off.
Now, companies want to keep adding capacity and maintain control of it, but are increasingly structuring deals to reduce the impact on financial statements, which helps limit the risk they’ll be seen as overexposed.
The hyperscalers are starting to use so-called synthetic leases, which limit the liabilities that appear on their balance sheet but still allowthem to benefit from tax relief on depreciation, according to Jeffrey Shell, a vice chairman of corporate capital markets at CBRE.
Tech giants would previously just write their own checks “because they need to move quickly for first mover advantage,” said Shell. “At some point, even for the biggest companies, financing at these levels has a meaningful impact on the balance sheet.”
As borrowing soars, credit markets are having to adapt to cope with the demand.
“The size has now outstripped what you’re going to realistically place into CMBS, ABS, and the private placement project bond market,” said Scott Wilcoxen, JPMorgan Chase & Co.’s global head of digital infrastructure investment banking. “It’s going to take all of them.”
At least $175 billion of data-center related US credit deals have been struck this year so far, according to figures compiled by Bloomberg News. Oaktree’s Marks questions the yields on the debt that’s been sold by hyperscalers to finance the AI investments. Play Video
The spread is sometimes only about 100 basis points higher than US Treasuries, leaving the investing veteran wondering whether it’s “prudent to accept 30 years of technological uncertainty to make a fixed-income investment that yields little more than riskless debt?”
And not everyone is a fan of the design of some of the vehicles that investors are being asked to put money into.
“We’ve seen master trust structures where the assets can be rotated every few years,” said Michelle Russell-Dowe, co-head of private debt and credit alternatives at Schroders Capital. “It’s hard to underwrite so we don’t like those.”
Mentions of bubbles have seen regulators take an interest. The Bank of England is reviewing lending to data centers after growing concerned at the level of spending and financing.
According to JPMorgan’s Wilcoxen, one phrase that keeps popping up in the market to describe the vast expanse of financing being tapped is “everything everywhere all at once,” a riff on the recent Oscar-winning movie.
“The amount of money that is chasing all this is extraordinary,” he said.
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