Meta grew advertising revenue 27% year over year to $59.4 billion in Q2. Total revenue was up 28% to $60.8 billion for the three months ended June 30.
Revenue landed above expectations. The stock slid anyway — earnings came in under Wall Street's targets, and the Q3 forecast disappointed investors.
Executives sought to allay concerns by underscoring Meta's juggernaut status in digital advertising and how AI is enhancing monetisation efficiency.
CEO Mark Zuckerberg told analysts:
"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."
Advantage+, Meta's AI-powered suite of ad products, continues to gain steam and reached a $75 billion annual revenue run rate in Q2.
The quarter also saw the rollout of the Meta Generative Recommender, which CFO Susan Li described as a "paradigm shift" in how the platform runs ads.
"Rather than scoring every possible ad individually, we are now using [large-language models] to reason about ad content and user preferences together, and predict the best ad for each person. This makes our ad matching more intelligent and more precise, which compounds performance gains for advertisers."
The shift is from evaluating ads one at a time to reasoning about creative and user together.
Meta forecast Q3 revenue in the range of $61 billion to $64 billion. Li cited two factors:
Meta narrowed full-year capital expenditures to $130 billion to $145 billion, against a prior estimate of $125 billion to $145 billion. The bottom of the range moved up — signalling that the spending floor is no longer negotiable.
Forrester Vice President and Research Director Mike Proulx was blunt:
"Meta believes AI infrastructure is now a strategic asset, but its bill is arriving faster than the payoff. Meta's ad business is still a monster, but everything else got more expensive. Revenue beat expectations and engagement continued to grow, but what it generated in cash this quarter almost all got eaten by AI infrastructure spending. Investors now have to decide whether Meta's growing list of AI initiatives represents company diversification or distraction."
Meta made some strides diversifying in Q2. "Other" revenue for the family of apps was up 73% year over year to hit $1 billion for the first time, driven by stronger demand for WhatsApp paid messaging and subscriptions.
At Meta's scale, though, $1 billion can feel like a drop in the bucket — and investor attention is fixed on capital expenditure right now.
Some researchers expect Meta could surpass Google in ad revenue for the first time this year. That said, Google has a wider range of business drivers, including a cloud segment booming amid the AI bonanza. For Google's quarter see Google's Ad Revenue Hits $81.6B: "AI Is Additive to Search, Not a Replacement", and for Amazon's see Amazon's Ad Revenue Hits $19.8B, Up 26% — Multisport Advertisers See 2.3x Reach.
Audit your Advantage+ dependency. A $75 billion run rate means Meta has committed to this automation stack. Relative support and performance for manual campaigns will likely keep sliding.
Plan for reduced personalisation in Europe. The CFO named it as a headwind directly. Campaigns leaning on European targeting should have a degraded-performance scenario ready.
Translate the "paradigm shift" into creative strategy. If the model reasons about ad content itself, the meaning and context of your creative matter as much as your targeting settings. Creative effectively becomes a targeting signal.
For how Meta's AI bet reads against the company's track record, see Will Meta's Massive AI Bet Pay Off? Look at How the Company Actually Grew.
$59.4 billion, up 27% year over year. Total revenue rose 28% to $60.8 billion for the three months ended June 30.
Earnings came in under Wall Street targets, and Q3 guidance of $61–64 billion disappointed investors. Skepticism about Meta’s large AI spending also persists.
Meta's AI-powered ad product suite reached a $75 billion annual revenue run rate in Q2.
Instead of scoring every possible ad individually, it uses large language models to reason about ad content and user preferences together and predict the best ad for each person. The CFO called it a paradigm shift.
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