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Meta reached 3.43 billion daily active users across its family of apps in early 2025, yet its market cap ballooned to over $1 trillion not through user growth but through AI integration. The company's Llama models and Meta AI assistant—approaching 1 billion monthly users—represent phase transitions in business model evolution: from social graph monetization to AI infrastructure that touches every product surface.

The transformation mirrors how ecosystems shift from one stable state to another through positive feedback loops. As Meta AI usage grew 70% year-over-year in advertising campaigns (now $20 billion annual run rate), the company reinforced its dominance through data network effects—each interaction training models that make subsequent interactions more valuable. This created lock-in effects competitors can't replicate: switching costs increase exponentially when AI personalization adapts to individual behavior patterns.

Meta's $64-72 billion capital expenditure plan for 2025 (mostly AI data centers and 1.3 million GPUs) reveals the metabolic cost of maintaining dominance in winner-take-all markets. The company can't stop investing without ceding ground to competitors, but the scale required—building a Louisiana data center complex larger than most tech companies' entire infrastructure—creates barriers new entrants can't match. This is preferential attachment operating at infrastructure scale: those with resources attract more resources, while smaller players face insurmountable entry costs.