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S&P Global revises Meta's outlook to 'negative' on AI spending, cash flow concerns

S&P Global revises Meta's outlook to 'negative' on AI spending, cash flow concerns

On October 30, S&P Global Ratings downgraded Meta Platforms' outlook to negative from stable, citing significant concerns about the social media giant's capital spending and operating cash flow. The tech sector has historically been heavy spenders in cloud computing, online advertising, and e-commerce, but the AI boom has led to soaring capital expenditures, causing investors to question whether these industries can generate returns swiftly enough.

In the third quarter, Meta projected annual capital expenditure between $135 billion and $145 billion, following a free cash flow deficit of $2.12 billion. To fund its AI expansion, Meta plans to sell $97.5 billion in stock. While Meta can monetize its AI investments less than its competitors, it remains uncertain when its revenue streams will surpass rising costs over the next few years.

According to S&P, Meta will generate a free cash flow deficit of $39 billion in 2026 and $71 billion in 2027. The agency warned that elevated spending could keep these deficits negative beyond 2028, expecting Meta to finance its 2028 cash shortfall entirely through debt. Given the uncertainty surrounding Meta's future capital expenditures and its ambitious AI investment plans, S&P expressed less confidence that it will curb spending as previously anticipated.

This increase in leverage could push the company's leverage above 1.0x as early as 2027, placing it above S&P's threshold for the AA- issuer credit rating. Meta's leverage rose to 0.1x in 2025, largely due to its strategy of leasing data-center capacity instead of issuing debt. S&P's US media and telecom sector lead, Naveen Sarma, noted that if capital expenditures remain high and continue growing faster than expected, credit profiles will continue to deteriorate, and cash flows will remain negative.

Written by urgent.news from Channel News Asia's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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