Over the past two weeks, Alphabet, Amazon, Meta and Microsoft announced capital expenditure plans totaling more than $740 billion for this year, which Wall Street is treating largely as spending on AI infrastructure such as data centers and chips. Early in the AI boom, investors often rewarded these large outlays as a sign of confidence in the technology's growth prospects. As the fourth quarter arrives, however, that optimism is giving way to worries about negative free cash flow (spending more cash than a company generates), rising debt levels and whether such massive investments will ever deliver sufficient returns.
Market reaction and key figures
Investor anxiety showed up in markets on Friday: the Nasdaq fell 2.9%, and chip stocks were hit hard — Nvidia dropped 4%, Broadcom more than 5%, and Qualcomm 11%. Alphabet experienced particularly sharp declines: its stock plunged 12% on Thursday, its worst day on record, erasing about $500 billion in market value; it fell again on Friday.
Why this is worrying — company examples
Alphabet provided the clearest example of how AI spending can strain formerly cash-rich businesses. Google’s parent company reported negative free cash flow of $9.1 billion in the third quarter, its second consecutive quarter in the red, while quarterly capex rose to $51.4 billion. Alphabet expects to spend up to $205 billion this year and anticipates that spending to rise further in 2027.
At the same time, the success of Google’s AI Mode — a chatbot feature built directly into Search — is starting to erode the company’s cash cow. Google Search advertising, which accounts for roughly half of the company’s revenue, slowed to 12% growth, its weakest pace in five quarters. That creates a tension: Google is spending billions on AI that could undermine the search business that funds those investments.
Amazon faces a similar situation: it reported negative free cash flow of $42.4 billion over the last 12 months, compared with $14.8 billion of positive free cash flow the prior year. The company says it expects to spend $220 billion in capex this year. Although revenue at Amazon Web Services grew 39%, Amazon’s stock fell 7% after the earnings release.
Meta is also burning cash: it reported negative free cash flow of $2.1 billion in the third quarter as capex outpaced operating cash. The company is guiding to as much as $145 billion in capex this year. Meta noted that Muse, its new free personal AI agent, is expensive to run — CEO Mark Zuckerberg has said it is “very compute-intensive to run.” Ad revenue grew 26%, but that positive news did not prevent Meta’s shares from dropping about 10% last week.
Microsoft was the lone exception on free cash flow among these firms, reporting $18.6 billion in positive free cash flow in its latest quarter, with capex at $45.2 billion, below the $50 billion it had projected. Microsoft said the lower capex was not an intentional pullback from AI spending but reflected delays in capacity from third-party providers. Shares of smaller companies that lease AI compute power sank as a result.
Financing: not just from profits
The funds to pay for this AI infrastructure are not coming solely from Big Tech profits. They also appear through equity and bond issuance. According to S&P Global Market Intelligence, Microsoft, Alphabet, Amazon, Meta and Oracle raised a combined $326 billion in debt in 2026, triple the amount raised the previous year.
What this means for other AI companies
Demand for AI compute remains strong — Google, Amazon and Microsoft all saw gains in their cloud businesses — but investors are increasingly nervous about the cost of meeting that demand. Those concerns could complicate the planned IPOs and financing of other AI firms.
Anthropic’s planned public listing is a case in point. The AI company filed to go public earlier this week, and its future growth depends on securing very large amounts of compute. The Financial Times reported on Friday that Blackstone warned investors Anthropic might not qualify for an investment-grade rating after its IPO, which could leave it more reliant on hyperscalers and third parties to fund its infrastructure ambitions.
