Michael Burry Warns AI-Linked Private Credit Could Become Source of Broader Financial Contagion

Investor Michael Burry, best known for predicting the 2008 U.S. housing market collapse, has renewed his warnings about the artificial intelligence boom, noting this time that mounting exposure to AI-related debt within the private credit market could become a significant source of financial instability.

In a post on his Substack, the Scion Asset Management founder said he is increasingly concerned about private equity firms that have acquired insurance companies and filled their balance sheets with illiquid, asset-backed securities, many of which are tied to financing the rapid expansion of AI infrastructure.

Burry’s latest comments extend a series of warnings he has made this year about what he considers excessive speculation in artificial intelligence, particularly the surge in financing for data centers, semiconductor manufacturing and AI computing infrastructure.

“The Big Short” investor highlighted a research paper examining how private equity firms have increasingly used insurance companies to hold complex credit instruments, arguing that a growing share of those investments are now linked to AI-related assets.

“Those asset-backed assets and structured securities are increasingly coming off data center and chip leases,” Burry wrote.

“This is where the possible contagion takes down the economy – by withdrawing funding for the data center buildout, which is also an increasing part of United States economic growth.”

His warning emerges amid concerns that the AI investment boom is no longer being financed primarily through equity capital but increasingly through private credit markets, where lenders provide financing outside the traditional banking system.

Private credit has expanded rapidly over the past decade as investment firms stepped in to provide loans that banks have become less willing to originate following tighter post-financial crisis regulations. As technology companies race to build massive AI data centers equipped with advanced semiconductors, the sector has become one of the fastest-growing borrowers in private credit markets.

Much of the financing supports expensive infrastructure, including data centers, servers, networking equipment and long-term semiconductor leasing arrangements, creating a new class of asset-backed securities linked to AI development.

Burry argues that this growing concentration could amplify risks if AI investment slows or financing conditions tighten.

His concerns also center on the role of insurance companies. Private equity firms have increasingly acquired insurers because their steady stream of premium income provides a large pool of capital that can be invested in higher-yielding private assets.

Critics have believed that some insurers are assuming greater exposure to illiquid investments than traditional insurance portfolios historically carried, potentially increasing financial risks during periods of market stress.

According to the paper cited by Burry, insurers occupy a unique position within the financial system because policyholders are protected by state guaranty associations if an insurer fails. That means losses from risky investment strategies could ultimately be absorbed through mechanisms supported by the broader insurance industry and, indirectly, taxpayers.

The paper argues that such a structure could “socialize losses more sharply than banking’s federal deposit insurance” if widespread failures were to occur.

Burry said persistently elevated interest rates could become the catalyst that exposes those vulnerabilities.

“Higher rates for longer could prove a catalyst,” he wrote.

“The 10-year Treasury closed today yielding 4.68%. That is not acceptable to the PE boys, who have been holding their collective breath for a long while now.”

Higher bond yields generally increase borrowing costs while reducing the value of existing fixed-income assets. For highly leveraged private equity firms and private credit investors, sustained high interest rates can make refinancing more expensive and reduce returns on debt-funded investments.

Burry noted that the sharp rise in Treasury yields over the past five years has made many debt-driven financing models increasingly difficult to sustain.

He argued that private equity firms have continued postponing the consequences of those higher financing costs.

“Nothing virtuous about this process,” Burry wrote.

“This is Private Equity kicking its final can down to the end of that very long road. Taxpayers wait there.”

The assertion is consistent with Burry’s increasingly skeptical view of both artificial intelligence and private markets.

Earlier this year, he described AI as a speculative bubble and disclosed bearish positions against several companies viewed as major beneficiaries of the AI boom, including Nvidia and Palantir Technologies. He has also argued that both the private equity and private credit industries are approaching what he called the “end of the road” after years of rapid expansion fueled by inexpensive financing.

Burry’s concerns come as spending on AI infrastructure reaches unprecedented levels.

Major technology companies, including Microsoft, Amazon, Alphabet and Meta Platforms, have collectively committed hundreds of billions of dollars to expanding AI data centers and computing capacity. At the same time, chipmakers such as Nvidia, AMD and Intel have benefited from surging demand for processors that power generative AI models.

Much of that investment has been supported not only by public equity markets but also by private financing, infrastructure funds and structured credit products. Supporters of the AI investment cycle believe that demand for computing power remains strong enough to justify continued spending, pointing to accelerating enterprise adoption of generative AI and cloud-based services.

Burry, however, suggests the growing reliance on leveraged financing creates a potential vulnerability. If higher interest rates, weaker economic conditions or slowing AI demand reduce investment in data centers, financing for new projects could dry up, affecting lenders, insurers and other institutions exposed to AI-linked debt.

While his warnings represent one investor’s assessment rather than a consensus market view, they highlight growing scrutiny of the financial structures supporting the AI boom.