Meta, once the poster child for social media dominance, has recently stepped into the AI arena with a flurry of product launches and hefty R&D budgets. The company’s quarterly filings reveal a dramatic uptick in AI-related spend, with the AI sub‑budget climbing from roughly $1.2 billion last year to over $2 billion this quarter. While the move is framed as a strategic pivot toward “generative” technologies, the lack of clear, market‑ready offerings has left investors uneasy. Wall Street analysts argue that the current trajectory resembles a “spend‑and‑hope” model, where capital is poured in without a solid roadmap for monetization.
The skepticism is amplified by Meta’s recent product performance. Features such as the AI‑driven ‘Reels’ enhancements and the experimental chatbot integrations have seen limited user adoption compared to the hype. In addition, the company’s internal AI teams are reportedly grappling with data‑privacy constraints and algorithmic transparency concerns, which could delay the launch of profitable services. Competitors like OpenAI and Google have already monetized their language models through APIs and subscription tiers, giving Meta a lagging edge in the race for AI revenue streams.
Looking ahead, Meta’s leadership faces a critical decision: either double down on AI R&D and risk further dilution of capital, or recalibrate its strategy to focus on incremental, revenue‑driven product iterations. Hedge funds and institutional investors are calling for a more disciplined spend schedule and clearer milestones, while the company’s top executives emphasize the need for long‑term innovation. The coming months will be telling, as Meta pitches its next wave of AI tools to a market that is increasingly demanding tangible returns on digital transformation investments.
Want the full story?
Read on TechCrunch →