KKR warns of growing credit market risks from AI borrowing spree

Global credit markets could face significant volatility if there is a downturn in the booming AI sector, as rising debt levels among tech borrowers leave investors exposed to “an unusually concentrated investment cycle”, KKR warned in a report on Wednesday.

With tech firms projected to pour nearly $8tn into AI infrastructure by 2030, a fifth of the investment-grade index — historically home to some of the safest securities — could end up being exposed to AI risks, said the New York-based investment firm, which manages $796bn across private equity, private credit and other markets.

It added that the true extent of AI exposure could be much bigger because of the growing use of off-balance-sheet financing, meaning that many portfolios could have a greater weighting in the sector once credit guarantees, leases and other future commitments are included.

“We don’t think enough people are talking about the potential volatility if AI growth slows,” Christopher Sheldon, co-head of credit and markets at KKR, told the FT. “This is multiples on trillions of dollars of market value. The knock-on effects across the broader markets could be very meaningful.”

Tal Reback, managing director at KKR and co-author of the report, pointed to “a market in which seemingly distinct exposures are increasingly driven by the same underlying economics”.

The warning comes amid growing concern among some investors over the extent of the tech sector’s borrowing spree, which is tapping every corner of the credit market, from highly rated investment-grade bonds to junk debt and securitised products, and reshaping the way the world borrows money in the process.

Scepticism among some analysts that the huge AI investments will eventually pay off has already hit the share prices of some high-flying stocks in the sector, while there are also fears that tech companies funding each other could amplify any industry fallout.

In recent months, investors have demanded higher yields for AI-linked debt to compensate for the increased risks. In a sign of investor nerves, data centre loans linked to Oracle have come under strain recently because of construction delays and permitting challenges, prompting scrutiny of the backstop provided by hyperscalers.

“We are having more conversations with LPs [investors] and insurance companies about how much AI exposure is prudent,” Sheldon said. “Investors should be mindful of overexposure and concentration because correlations are higher across this AI ecosystem.”

AI-linked debt currently amounts to about $600bn, or around 6.3 per cent of the US investment-grade market. In comparison, the highest sector exposure in the index was only 2.6 per cent on average over the past 29 years, KKR found.

Even if the largest hyperscalers, including Oracle, Amazon, Meta, Google, Microsoft and SpaceX, each hit a maximum index weighting of 3 per cent — the typical single-issuer limit for a bond portfolio — they could only raise up to $1.7tn from the high-grade bond market, leaving more than $6tn of expected capital expenditure unfunded, it added.

John Queen, a fixed income portfolio manager at Capital Group, said he had been closely monitoring the overall AI concentration as Big Tech firms issue debt across various asset classes.

“It’s a super important part of the puzzle,” Queen said. “If you aren’t paying attention, you could end up with more significant issuer concentration than you wanted.”

Unlike the equity market, where investments in AI hyperscalers could potentially be rewarded by massive gains, debt investors’ upside is limited.

“If you didn’t have exposure to these hyperscalers in the equity market, you’d be massively underperforming,” Sheldon added. “If you think about the credit markets, you’re not necessarily getting paid to take that concentrated bet right now.”

Investors needed to pay close attention to structural details, particularly for deals traded in the secondary market where there might not be full visibility on contract terms, including underlying lease, Sheldon said.

“We’ve walked away from deals where we couldn’t get comfortable with the lease terms and force majeure clauses,” he said. “If the lease isn’t well structured, [a counterparty’s] credit quality only gets you so far.”