S&P Downgrades Meta Outlook Over AI Spending

Meta Platforms faces increased scrutiny over its financial strategy after S&P Global Ratings revised the company's credit outlook from stable to negative on October 30, 2026. The decision reflects concerns about substantial artificial intelligence investments, rising capital expenditures and weakening cash generation.

Although Meta maintained its AA- credit rating, the negative outlook signals uncertainty about its ability to finance expanding AI operations while maintaining strong financial performance. S&P's highest rating is AAA, while ratings below BBB are classified as speculative-grade debt.

The ratings agency highlighted uncertainty surrounding Meta's growing capital expenditures and negative free cash flow. It also questioned whether the company's investments in artificial intelligence would generate sufficient returns compared with the costs of developing and operating the technology.

S&P Global Ratings specifically raised concerns about "Meta's ability to monetize its AI investments" as technology companies across the industry commit substantial resources to data centers and other AI infrastructure.

The agency also noted that the commercial potential of Meta's recently introduced Muse AI agent application and associated foundation models remains uncertain.

S&P Global Ratings said "it is unclear when these revenue streams will generate material contributions that exceed their rising costs over the next few years."

Meta disputed the assessment, maintaining that its artificial intelligence strategy offers significant commercial opportunities and supports its financial position.

"We respectfully disagree with S&P's assertion about Meta's AI monetization capabilities," a Meta spokesperson said. "We see significant product and business opportunities ahead of us, supporting our very strong credit profile."

The financial concerns follow Meta's third-quarter earnings report, which showed revenue growth of 26% but also revealed substantial spending commitments. According to the company's report, capital expenditures reached $34.9 billion during the quarter, exceeding operating cash flow.

Meta also recorded negative free cash flow of $2.12 billion, marking the first time the company entered negative territory on this measure. The company projected full-year capital expenditures of between $135 billion and $145 billion.

Investors reacted negatively despite the revenue performance. Meta shares declined 7% following the earnings announcement on October 22, while the stock finished October down 15%, its worst monthly performance in four years.

The company subsequently announced plans to raise $95 billion to finance its artificial intelligence initiatives. The fundraising strategy includes an initial $35 billion through underwritten public equity offerings, followed by another $60 billion through an at-the-market offering program.

S&P Global Ratings expects Meta's capital expenditure growth to begin "flattening out beginning in 2028," although the agency remains cautious about the company's spending trajectory.

The agency is "less certain that it will curtail its spending as previously anticipated." This uncertainty reflects questions about how quickly Meta can translate its infrastructure investments into sustainable revenue.

The broader technology sector is facing similar investor pressure as major companies expand their AI budgets. Microsoft, Alphabet, Amazon and Intel also face scrutiny over whether their infrastructure commitments can produce sufficient commercial returns.

Drew Matus of MetLife described the investment environment as difficult for major technology companies. He argued that businesses face criticism whether they reduce or increase capital expenditures, as investors demand clearer evidence that AI spending will support long-term growth.

Matus also questioned whether companies would execute their announced investment budgets within the expected timelines. He pointed to practical constraints involving the availability of workers, equipment and land needed to develop large-scale infrastructure.

He further observed that industries most exposed to artificial intelligence were increasing hiring rather than reducing their workforces. Meanwhile, Matus identified the concentration of AI investment, equity market gains and consumer spending within the broader economy as a concern.