Markets
July 22, 2026
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- AI stocks debt is flashing two warning signs as Big Tech hidden debt reaches $1.65 trillion while margin debt 2026 climbs to Dot-Com bubble levels, adding to AI bubble warning concerns despite an S&P 500 overvalued market
- Meta alone carries $420B in hidden debt, nearly triple its official books, while Oracle’s off-balance-sheet liabilities hit $273B, up 30x in four years tied to its Stargate project with OpenAI
- If AI demand misses, $1.65T in hidden debt converts to recorded losses while margin calls force selling in the same stocks simultaneously, with both risks activating at once
The race to build and conquer the rising AI narrative is now heating up. Companies across the world are now racing and indulging in cutthroat competitions to own sturdy AI infrastructure. The stock market’s inflated metrics, coupled with the S&P 500 overvalued numbers, are mirroring the emerging AI wave narrative. As this race heats up, a noteworthy Nikkei find has captivated the attention of investors after delivering a big tech hidden debt insight. The findings have revealed financial statements from Amazon, Meta, Alphabet, Oracle and Microsoft, unveiling AI stocks debt of a staggering $1.65T. This development is already being labeled as AI stocks debt that’s written off record as companies race towards banking on the brewing AI narrative.
Meta’s $420B and Oracle’s $273B Off-Balance-Sheet Debt Are the Numbers Wall Street Isn’t Pricing In
The recent Nikkei analysis has brought forth interesting insights, showcasing the big tech hidden debt that the major AI companies have been piling on as of late. Financial statements of Amazon, Meta, Oracle, Microsoft, and Alphabet have collectively revealed AI stocks debt worth $1.65T. This number has grown 8x since 2022 and has now become a significant matter of debate among investors and analysts. What’s interesting is the fact that this debt was hidden off-sheet, with the companies exceeding the on-balance-sheet debt of roughly $1.35T.
More importantly, per the findings, Meta and Oracle have ended up accumulating massive AI stocks debt. To win the ongoing AI race, both companies have ended up amassing $420B and $273B in big tech hidden debt, wanting to progress ahead in the current AI infrastructure path. In doing so, Meta has managed to inflate its debt three times more than its reported debt, with Oracle’s hidden debt having increased 30 times in more than four years.
The AI stocks debt explained above was classified as off-balance-sheet debt under Nikkei’s analysis. Off-balance-sheet debt refers to financial obligations that do not appear as traditional debt. Instead, they are often disclosed in footnotes rather than recorded as conventional borrowings.
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What This Off-Balance Sheet Debt Means for AI Companies
For companies in the AI sector, this AI stocks debt has been arranged through long-term leases for data centers, acquisitions of GPUs, financing for infrastructure, and collaborations with private credit firms. The magnitude of these financial commitments surpasses the amounts revealed by Nikkei. According to Morgan Stanley, the overall off-balance-sheet liabilities of the AI industry have now reached approximately $1.8 trillion, encompassing purchase agreements, long-term leases, and supplier financing related to the surge in AI infrastructure. Meanwhile, the Shiller CAPE ratio has risen to 41.5, marking its second-highest reading in the past 140 years, following only the 44.2 peak seen during the Dot-Com bubble in March 2000. The 10 largest S&P 500 stocks now account for a record 41.2% of the index, concentration driven largely by AI-linked names.
One of the clearest examples is Meta’s Louisiana AI data center, where the company holds a 20% equity stake while Blue Owl Capital finances the remaining 80% through debt. This type of arrangement allows companies to expand AI infrastructure without taking on the full debt directly on their balance sheets, making it a textbook example of the shadow borrowing highlighted by the Bank for International Settlements.
Why Rising Margin Debt 2026 Could Become a Potential Market Risk
The companies in today’s world and age are committing billions to AI infrastructure. These companies strongly believe that demand for AI will continue to rise and that AI bubble warning concerns are overblown. However, several key industry leaders have warned that an AI bubble could become a reality in the near future.
Jamie Dimon has compared the AI boom to the early days of the internet, when companies like Yahoo and Netscape faded while others like Google and Facebook won later, suggesting the payoff from AI may not arrive on the timeline investors currently expect.
More importantly, the excessive purchase of AI infrastructure may end up hurting returns on invested capital, provided that the demand for AI declines in the near term. This development could further lead the firms to asset write-downs or impairments, leading to lower profits and higher liabilities. These AI stocks debt obligations may in turn affect investor sentiment, accelerating the stock sell-off in the future.
The risks associated with AI stocks debt are also amplified by record investor leverage. US margin debt 2026 has risen to $1.53T in June, supporting the surging AI narrative and now approaching levels last seen during the Dot-Com bubble. With margin debt in 2026 hitting historic highs, any broad sell-off in AI stocks may trigger a severe market impact, significantly affecting leveraged investors.
Leuthold Group Chief Investment Officer Scott Opsal, speaking to CNBC, described the current level of margin debt in blunt terms:
“This is very bearish looking. When people get too enthusiastic, too tolerant of risk, too greedy, things usually roll the other direction.”
Opsal’s warning underscores the core risk at the heart of this story: the same borrowed money fueling AI stock gains could just as easily accelerate their decline.
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