The breakneck buildout of artificial intelligence data centers is rapidly becoming one of the biggest stress tests the global insurance industry has faced in years, as unprecedented capital flows, complex financing structures, and the blistering pace of technological change create both enormous opportunities and hidden vulnerabilities.
CNBC reports quoting McKinsey that global spending on data centers could reach $7 trillion by 2030, and hyperscalers such as Microsoft, Google, and Amazon can no longer shoulder the burden alone. Big Tech is increasingly turning to private equity, private credit, debt markets, and sophisticated off-balance-sheet structures to fund the capital-intensive projects.
Private infrastructure data center deals routinely exceeded $10 billion last year, according to Preqin data, with the largest single transaction reaching $40 billion — a consortium involving Nvidia, Microsoft, BlackRock, and Elon Musk’s xAI to acquire Aligned Data Centers.
“When you put $10 to $20 billion plus in a single location, it creates capacity issues in the marketplace,” Tom Harper, data center leader at insurance broker Gallagher, was quoted by CNBC as saying about the situation.
He added that the insurance industry 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 sheer scale has made providing adequate capacity extremely challenging.
Harper noted that in 2023 it was “nearly impossible to reasonably insure a $20 billion campus.” By 2026, such conversations will have become routine.
“We’re talking about trillions of dollars,” he said, “and almost going back to the same cycle where there’s almost no transparency about the financing structures — the scale is astronomical.”
Rajat Rana, a partner at Quinn Emanuel Urquhart & Sullivan who worked on structured finance litigation after the 2008 financial crisis, drew a direct parallel to the housing bubble.
“This is the largest peacetime investment project in human history, which is financed largely off balance sheet,” he told CNBC. “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.”
The surge in demand is also accelerating innovation in power generation and semiconductor technology, creating a double-edged sword for insurers and lenders. Facilities require highly specialized coverage that blends traditional real estate risks with bleeding-edge technological assets. Some of the world’s largest insurers have created dedicated data center practices to underwrite these projects.
Harper explained that the concentration of value, the massive power requirements, and the advanced technology typically result in advantageous pricing, making data centers “very desirable” for insurers. However, problems arise when $20 billion worth of assets sit in high-wind or hurricane zones. Supply chain issues add a separate challenge, as clients import enormous shipments of high-value equipment that often sit in third-party warehouses before installation.
The M&A frenzy has kept transactional lawyers busy. According to the report, Kirkland & Ellis has noted that several companies are now forming dedicated data center teams spanning real estate, power, telecom, finance, insurance, trade, private equity, and cybersecurity. Marsh launched a dedicated digital infrastructure advisory group to help clients navigate increasingly complex contracts.
Last year, Marsh also created Nimbus, a €1 billion ($1.2 billion) insurance facility for data center construction in the UK and Europe, which it expanded just seven months later to offer limits of up to $2.7 billion.
Alex Wolfson, senior vice president of credit specialties at Marsh Risk, said private credit is playing a growing role.
“Private credit can meaningfully complement banks and can support non-hyperscale contracted offtakes,” he said.
As data center loans proliferate, however, insurers providing credit protection are beginning to hit capacity limits, prompting Marsh to develop new solutions for lenders.
Rana warned that the opacity of off-balance-sheet financing makes it difficult for insurers and investors to fully understand the risks. In January, four U.S. senators urged the government to investigate how Big Tech is borrowing “staggering sums of cash” through complex debt markets, warning that such leverage could lead to “destabilizing losses” for financial institutions and trigger a broader crisis.
Rana noted in a March report that this lack of transparency could create second-order litigation risks for pension funds, insurers, and asset managers invested in private credit vehicles if concentration risks later materialize.
He has already fielded concerns from private equity funds about commercial leases and property valuations. Tenants are pushing for lease extensions while landlords seek higher rents to reflect the premium value of AI-ready facilities.
“I’m not a doomsday guy who’s saying, hey, it’s gonna crash,” Rana said. “My point is, whether it crashes or not, the disputes are inevitable, and we have already seen those disputes.”
A particularly thorny debate centers on the so-called “GPU debt treadmill.” Data centers are built to last decades, but the high-performance GPUs that power them have an average useful life of only about seven years.
CoreWeave, a cloud provider of AI infrastructure, became the first company to secure investment-grade GPU-backed loans last week, raising $8.5 billion and sending its stock up 12%.
Rana described the mismatch as a “treadmill,” first coined by AI commentator Dave Friedman.
“This is almost like a treadmill that these AI data centers are running on,” he said.
Even ring-fenced, investment-grade structures may mask longer-term credit risks as operators repeatedly raise fresh debt to upgrade equipment and build new facilities.
“There are different data centers that are raising debt by disclosing different life cycles to investors,” Rana said. “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?”
Harper noted that the rapid evolution of GPU lifecycles has forced Gallagher to get creative with bespoke insurance policies that include pre-agreed valuation methods.
“It would be a nightmare with the size and scope of these [facilities] to determine [the value of] each individual unit,” he said.
Insurers have observed operators responding by building more modular facilities in anticipation of shorter equipment cycles.
Alex Wolfson of Marsh Risk summarized the core tension, saying: “Lenders typically want asset lives that exceed loan tenors by a comfortable margin, and the shorter useful life of GPUs challenges that assumption.”
As a result, lenders are structuring deals more conservatively to protect themselves.
The AI data center boom is reshaping the insurance industry in real time. What began as a specialized niche has become a multi-trillion-dollar stress test that is forcing underwriters, brokers, and lawyers to develop new products, risk models, and legal safeguards.
The development represents one of the largest growth opportunities in a generation for insurers willing to embrace the complexity. For those who misjudge the risks hidden in the opaque financing structures and rapid technological obsolescence, it could become a painful reminder of past bubbles.
