In 2022, investors punished Meta's stock for its Reality Labs CapEx. Today, the market applauds even larger AI-related spending (66% of MAG-5's operating cash flow). This signals a fundamental belief that AI investments translate directly to tangible near-term earnings, unlike speculative bets like the Metaverse.

While increased CapEx signals strength for cloud providers like Microsoft and Google (who sell that capacity to others), the market treats Meta's spending as a pure cost center. Every dollar Meta spends on AI only sees a return if it improves its own products, lacking the direct revenue potential of a cloud platform.

While the market seeks revenue from novel AI products, the first significant financial impact has come from using AI to enhance existing digital advertising engines. This has driven unexpected growth for companies like Meta and Google, proving AI's immediate value beyond generative applications.

The true financial windfall from AI won't come from hyped, "AI-native" companies like OpenAI. Instead, established giants like Meta and Amazon will generate massive shareholder value by applying AI to optimize their existing, scaled operations in areas like ad targeting, logistics, and robotics.

Meta's huge AI capex, despite no hit product yet, is based on proprietary data from its massive platform. Unlike the speculative Metaverse venture, this investment is a direct response to observed exponential growth in user engagement with AI content, even if users publicly claim to dislike it.

Meta's stock rose 8% after announcing a massive CapEx hike, while Microsoft's fell 5% despite strong results. This contrast reveals that investors currently favor bold, narrative-driven spending to capture AI market share over more measured, margin-focused growth, even when a company has a massive sales backlog.

Today's AI market differs from the dot-com bubble. Investors are rewarding companies with immediate earnings from AI infrastructure spending (semiconductors, power), rather than speculating on the long-term, uncertain productivity benefits for AI adopters.

According to SaaStr founder Jason Lemkin, the ultimate metric for judging whether an incumbent company has successfully integrated AI is not feature releases but growth re-acceleration. If revenue growth isn't picking up speed, the AI initiatives are merely performative. He points to Meta as a prime example of a company whose AI efforts are validated by this metric.

Seemingly small, quarterly AI improvements to Meta's ad platform (e.g., a 5% conversion bump) have a compounding effect. Performance marketers reinvest these gains back into the platform, creating a flywheel that reaccelerates revenue growth, explaining the stock's recent surge despite a mature business.