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    Home»Business

    AI spending threatens credit quality of Amazon, Meta, Alphabet

    AdminBy AdminJuly 25, 2026 Business
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    AI spending threatens credit quality of Amazon, Meta, Alphabet

    Magnificent 7 tech stocks on display at the Nasdaq.

    Adam Jeffery | CNBC

    The race to build artificial intelligence infrastructure at a trillion-dollar annual clip is eroding the free cash flow and increasing balance-sheet risk at so-called hyperscalers, warned Moody’s Ratings.

    In a research note released this week, Moody’s said that the spending surge is forcing even the world’s most cash-rich corporations like Alphabet and Microsoft to lean heavily on debt, stock sales and off-balance-sheet moves to fund their AI ambitions.

    “Previously, these companies relied on asset-light structures centered on software, intellectual property, and scalable cloud services that required modest capital investment,” Moody’s said in the Wednesday note. “The transition from asset-light to asset-heavy models requires unprecedented levels of investment and capital raising.”

    The moves “threaten credit quality” for the six companies tracked by Moody’s, which include Microsoft, Amazon, Alphabet, Meta, Oracle and CoreWeave, according to the report.

    The ratings firm projects that capital expenditures — or capex, which are investment for physical assets like data centers — will hit $785 billion in 2026 before reaching about $1 trillion next year.

    The shift breaks a decades-long Silicon Valley formula that created the world’s most valuable companies. Software costs little to replicate, yielding fat profit margins and fortress balance sheets. Generative AI, by contrast, demands a vast physical footprint: warehouses crammed with expensive and energy-hungry servers and chips.

    To finance the expansion, tech giants are increasingly turning to Wall Street, resulting in booming profits for the financial industry.

    Direct debt across the six hyperscalers has reached approximately $460 billion, according to Moody’s. Tech companies are also tapping public markets for cash, including Google-parent Alphabet, which last month announced an $85 billion equity sale.

    Leasing data centers

    The ratings firm noted that because AI hardware and infrastructure require massive up-front investment while revenue materializes over a longer time horizon, free cash flow across the sector is coming under pressure.

    To keep direct debt off their balance sheets, hyperscalers are leaning on off-balance-sheet financing, mostly through long-term data center leases, the report explained.

    Moody’s said that lease commitments across the group have ballooned to $1.2 trillion. More than $820 billion of that total is from leases that haven’t started yet, meaning the data centers are still being built.

    While these obligations don’t show up as traditional debt, Moody’s says it considers them as debt-equivalent liabilities that will bind companies to significant rent payments down the line.

    Despite the warning, Moody’s noted that Microsoft, Alphabet, Amazon and Meta retain among the strongest corporate balance sheets in the world, making it unlikely that their investment grade ratings are under imminent threat.

    The immediate pressure is concentrated on lower-rated entities like Oracle and specialized AI cloud provider CoreWeave. Oracle carries a rating of Baa2 with a negative outlook, placing it just two notches above junk status.

    Meanwhile, CoreWeave operates within the high-yield market with a Ba3 rating, relying on complex private debt structures to finance its GPU hardware fleets.

    Circular ecosystem

    Moody’s also pointed to structural circularity within the AI boom. Some of the multibillion-dollar backlogs reported by hyperscalers stem from strategic deals with pre-IPO artificial intelligence labs including OpenAI and Anthropic, Moody’s noted.

    The firms have invested billions into AI labs that, in turn, spend heavily on cloud computing from those same companies, creating what Moody’s described as a circular AI ecosystem.

    The overlapping relationships heighten risks because many of the industry’s biggest companies are increasingly dependent on the same AI customers and the same assumptions about future demand, Moody’s said.

    Even so, the tech giants have significant strengths that help offset those risks.

    Demand for AI computing remains robust, cloud businesses continue to grow and hyperscalers have signed hundreds of billions of dollars in long-term customer contracts that should provide predictable revenue. Those deals support the industry’s largely-strong credit profiles, even amid the spending boom.

    Still, investors should recognize that the tech industry’s financial profile is undergoing a structural change unlike anything seen in the cloud era, according to Moody’s.

    “Investors will increasingly focus on these companies’ ability to realize an adequate return on investment,” the ratings firm said.

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