This article first appeared on GuruFocus.
Michael Burry (Trades, Portfolio) is warning that Big Tech’s unprecedented AI infrastructure spending could eventually leave hyperscalers with significant write-offs, arguing that today’s buildout is beginning to resemble earlier capital booms that ended with excess capacity and falling returns.
Burry said net capital investment by S&P 500 companies reached 2.07% of U.S. GDP as of June 30, the highest level in nearly four decades outside the aftermath of the March 2000 Nasdaq peak.
I have little doubt the next few quarters will set still higher and higher net investment/GDP marks, possibly even eclipsing that aftermath of the 2000 tech stock peak, Burry wrote.
His concern goes beyond current spending.
Burry estimates Microsoft (NASDAQ:MSFT), Amazon (NASDAQ:AMZN), Alphabet (NASDAQ:GOOGL), Meta Platforms (META) and Oracle (NYSE:ORCL) have accumulated roughly $3 trillion in purchase commitments, future leases, guarantees, construction-in-progress and other exposures tied to AI infrastructure.
When the write-offs come, perhaps in 2028 or 2029, these commitments discussed in Part IV may be so large that a relatively small write-off has a bigger impact than we can now imagine, he wrote.
Burry’s thesis rests on the capital cycle: heavy investment creates capacity, competition reduces returns, and weaker economics eventually force companies to impair or write down assets.
He pointed to the late-1990s technology, media and telecommunications boom, after which depreciation and write-downs helped push aggregate S&P 500 net investment below zero for 12 consecutive quarters between mid-2003 and mid-2006.
Oracle has become a particular focus of the concern. Burry questioned the company’s accounting around customer prepayments and future cloud revenue, while recent anxiety around Oracle’s debt and Project Jupiter data center has added to scrutiny of AI infrastructure financing.
Investor takeaway
For investors, Burry’s warning is less about whether AI demand exists and more about whether hyperscalers are building infrastructure at returns high enough to justify the commitments.
The critical metrics are free cash flow, capex intensity, utilization, depreciation, lease obligations and returns on invested capital.
If AI revenue continues scaling faster than infrastructure costs, the current spending wave could remain economically rational.