AI data center boom ‘stress tests’ insurers as private capital soars

AI data centers are becoming a “stress test” for insurers as rapid technological advancements and the use of increasingly complex financial structures present a unique set of challenges and opportunities for the sector.

Global spending on data centers could reach $7 trillion by 2030, according to McKinsey, and much of that spending can no longer come solely from hyperscalers. Instead, Big Tech is increasingly tapping private equity, private credit and using debt to finance the capital-intensive build-out of the facilities.

Private infrastructure data center deals were consistently above the $10 billion mark last year, according to data from Preqin. The largest deal amounted to $40 billion, with Nvidia, Microsoft, BlackRock and Elon Musk’s xAI forming part of a consortium of investors to buy Aligned Data Centers.

The fact that so much money is tied up in building, constructing, and running data centers has been a “real stress test” over the last four to five years for the major insurance companies, Tom Harper, data center leader at insurance broker Gallagher, told CNBC.

“When you put $10 to $20 billion plus in a single location, it creates capacity issues in the marketplace. The marketplace has always had an appetite for these risks because they are such high-quality builds. They’ve got cutting-edge technology, they’re AA plus plus construction locations, but the capacity — the ability to provide the insurance capacity at these locations — has been tough.”

It was nearly impossible to reasonably insure a $20 billion campus in 2023, according to Harper. In 2026, however, it’s become a weekly conversation.

Estimated spending on AI data centers has been referred to as the biggest peacetime investment project in history. Rajat Rana, partner at Quinn Emanuel Urquhart & Sullivan, told CNBC he would take it a step further and stress that this is the “largest peacetime investment project in human history, which is financed largely off balance sheet.”

Rana, who worked on structured finance litigation in the wake of the housing crisis triggered by the 2008 Financial Crash, said tracking developments in AI data center financing feels like “deja vu.”

“We’re talking about trillions of dollars, and almost going back to the same cycle where there’s almost no transparency about the financing structures — the scale is astronomical,” he said.

The AI boom is not only driving a rush in demand for the facilities, it’s also spurring rapid advancements in power generation and chips — the critical tech that the data centers house. The advancements and huge sums of money flowing into the sector pose both risks and rewards for insurers and lenders.

Data centers require a specialized approach from insurers, encompassing both real estate and technological assets. Some of the largest insurers in the world are creating data center specific avenues to manage the projects, Gallagher’s Harper said.

The facilities present unique challenges due to the high concentration in value, the required power generation and “bleeding edge tech,” which typically grants them advantageous pricing and makes them “very desirable,” Harper told CNBC.

Insurers want to spread risk, which drives costs down. But issues arise when you have $20 billion worth of assets concentrated in a high-wind or hurricane zone, he added.

Supply chain disruption can add complexity when it leads to a concentration of high-value equipment that is yet to be installed. Clients are importing large dollar amounts of shipments from overseas and then storing them — often in facilities they don’t own or operate — which introduces additional risk, he said.

The M&A boom is also keeping transactional lawyers busy, with Kirkland & Ellis noting that a number of companies are forming data center specific teams, enlisting specialists across real estate, power, telecom, finance, insurance, trade, private equity and cybersecurity.

Professional services firm Marsh launched a dedicated digital infrastructure advisory group designed to help clients as contracts become increasingly complex.

Last year, Marsh also launched Nimbus, a 1-billion-euro ($1.2 billion) insurance facility for covering the construction of data centers in the U.K. and Europe. Seven months later, it expanded the facility to offer limits of up to $2.7 billion.

“Private credit can meaningfully complement banks and can support non‑hyperscale contracted offtakes,” said Alex Wolfson, senior vice president of credit specialties at Marsh Risk.

As data center loans increase, insurers who protect lenders if a borrower doesn’t pay, are starting to hit limits, Wolfson explained. Marsh is working on solutions to support lenders.

However, Quinn Emanuel’s Rana cautioned that when it comes to data centers, it’s not easy for insurance companies to fully understand the risk as financing moves off the balance sheet.

He noted that in January, four U.S. senators called on the government to investigate how Big Tech is increasingly turning to “complex and opaque debt markets to borrow staggering sums of cash.” In an open letter, the senators warned that massive debt loads could cause “destabilizing losses” for financial institutions, triggering a broader financial crisis that harms the economy.

That increased opacity in financing can lead to second-order litigation risks for downstream investors such as pension funds, insurers and asset managers invested in private credit funds who later learn they were not fully aware of concentration risk, Rana said in a note published in March.

He told CNBC that some PE funds have reached out to him with concerns about commercial leases and the valuation of properties.

Tenants are trying to negotiate the extensions of their properties and landlords are disputing the value as they look for higher prices for AI data centers.

“I’m not a doomsday guy who’s saying, hey, it’s gonna crash. My point is, whether it crashes or not, the disputes are inevitable, and we have already seen those disputes,” Rana said.

A key debate around potential cracks in financing centers on GPUs and the risk that their lifecycles may not align with the longer lifespan of the facilities that house them.

CoreWeave, which sells AI tech in the cloud, is the first company to secure GPU-backed loans, essentially using the value of the high-performance chips as collateral. Last week, the company announced it secured $8.5 billion in a first investment-grade rated GPU-backed deal. Its stock jumped 12% on the day.

While data centers typically have a decades-long lifecycle, the average lifecycle of a GPU is around seven years.

“There are different data centers that are raising debt by disclosing different life cycles to investors,” said Rana. He referred to the problem as the “GPU debt treadmill,” a phrase coined by AI commentator Dave Friedman.

“This is almost like a treadmill that these AI data centers are running on,” Rana told CNBC. Even if the financing structure is ring-fenced and backed by an investment-grade counterparty, the real risk may lie in whether an equity issue today later evolves into a credit problem over time.

“As these new chips come in, the data centers will feel pressured to raise more debt, and then they will have to build new infrastructure, and then that basically creates a billion-dollar question: how fast can you build these facilities? How fast can you raise credit?”

The cost of funding these projects is likely to continue to fuel recent growth in asset-backed securitization deals, says Harper, with greater volumes of commercial mortgage-backed securities sold to investors.

For some insurers, like Gallagher, the changing dynamics in the sector are opportunities rather than challenges. Harper said the lifecycles of GPUs have been increasing. Where things have depreciated quickly, Gallagher has had to get creative and write bespoke insurance polices with a predetermined agreement on how to value the assets.

“It would be a nightmare with the size and scope of these [facilities] to determine [the value of] each individual unit,” he said.

Harper also stressed that GPUs are interchangeable. The firm has seen operators anticipate relatively short life cycles and construct facilities that are more modular in response.

“There is a core tension in data center project finance: lenders typically want asset lives that exceed loan tenors by a comfortable margin, and the shorter useful life of GPUs challenges that assumption,” said Marsh Risk’s Wolfson.

Lenders are therefore structuring loans more cautiously to protect themselves.