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Meta continues to insist AI spend is totally justified, potentially blowing over $8 billion on data centers
Just because Meta keeps saying AI is paying off doesn't necessarily make it true.
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Meta has just reported a second quarter revenue of $60.80 billion. Though this figure represents another record-breaking year-on-year increase of about 28%, shares are reportedly down by 10%. Seems like the AI money pits may be shifting beneath Meta's feet.
The company reported it had $784 million in free cash flow by the end of Q2 2026, but that represents a 91% year-on-year decrease compared to the $8.55 billion it had to throw around last year. Where did all that money go? Questionable spending on the company's VR and AR division, Reality Labs, is only part of the story. The rest can be attributed to Meta's AI infrastructure buildout.
Both Meta CEO Mark Zuckerberg and CFO Susan Li projected optimism to investors during the latest earnings call. Zuckerberg told investors, "Our investments in AI are accelerating every major part of our core business."
Zuckerberg offers the example of advertising, explaining, "We are using LLMs to improve how our systems predict and rank the ads that we show. We've expanded the context that we can take into account around a person's organic and ads activity to determine an ad's relevance, driving significant increases in relevance and conversions on both Facebook and Instagram."
The company was somewhat buoyed this past quarter by making $59 billion in revenue from advertising. Zuckerberg went on to say, "On a dollar basis, our ads business is reporting faster year-over-year revenue growth than any other company's reported ad business—so these AI investments are paying off."
Zuckerberg then said, "We see a large enterprise opportunity to sell to businesses, including APIs, business agents, potentially selling compute directly, and other services that we're building for large customers."
'Selling compute' would be one way to potentially see a return on outsized AI investment. Li elaborates, "The industry has under-built historically for the wave of AI adoption, making existing capacity, including our own, extremely valuable."
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