Amazon, Meta, Microsoft, and Other US Tech Giants Are Hiding $1.65 Trillion in AI Debt
A Nikkei Asia analysis says the liabilities are mostly tied to data center leases and hardware that appear in SEC filing footnotes.
- A study by Nikkei Asia found five American technology giants—Alphabet, Microsoft, Amazon, Meta, and Oracle—carry over $1.65 trillion in collective "hidden" debt, exceeding the $1.35 trillion officially reported on balance sheets.
- While legal under SEC rules, these firms use off-balance sheet arrangements similar to Enron to fund AI infrastructure, effectively hiding long-term data center leases and hardware costs from view.
- Oracle's obligations reached $273.3 billion as of May 2026, including a $27 billion Hyperion data center investment from Blue Owl Capital, while Meta carries roughly $420 billion in hidden debt.
- S&P recently downgraded Oracle's short-term rating from A-2 to A-3 and its long-term rating from BBB to BBB-, placing the company just one notch above junk status, as Morgan Stanley and Moody raise concerns.
- With four of the five companies set to report earnings in the coming days, investors are watching closely as Nikkei reports plans to sell new shares could trigger equity dilution and impact market confidence.
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Five Big Tech giants have $1.65 trillion in AI debt hidden from their balance sheets, Nikkei analysis finds - Tech Startups
The race to dominate artificial intelligence is creating a financial reality that doesn’t appear on the balance sheets of America’s largest technology companies. A new analysis by Nikkei estimates that five U.S. tech giants, Alphabet, Microsoft, Amazon, Meta, and Oracle, […] The post Five Big Tech giants have $1.65 trillion in AI debt hidden from their balance sheets, Nikkei analysis finds first appeared on Tech Startups.
Amazon, Meta, Microsoft, and other US tech giants are hiding $1.65 trillion in AI debt
According to estimates from Nikkei Asia, Alphabet, Microsoft, Amazon, Meta, and Oracle have together amassed roughly $3 trillion in total debt, a large share of it tied to exorbitant AI infrastructure spending – long-term data center lease agreements, along with costly servers, graphics accelerators, and other computing hardware that has...Read Entire Article
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