Big Tech AI Strategies

Strategy: Partner-first. Microsoft bet everything on OpenAI early and won the enterprise AI distribution game. Copilot is embedded across Office, GitHub, Azure, and Windows. The playbook: use OpenAI models while building internal capabilities as a hedge. Stargate partnership adds infrastructure scale.

Strategy: Vertical integration. Google owns the full stack: research (DeepMind), models (Gemini), chips (TPU), cloud (GCP), and distribution (Search, Android). The "AI-first" pivot is existential — AI threatens search, Google's cash cow. DeepMind's research leads to breakthroughs (AlphaFold) but product execution has lagged.

Strategy: Open source as competitive weapon. By giving Llama away, Meta commoditizes the model layer, preventing OpenAI/Google from charging monopoly rents. This protects Meta's real business: AI-powered ad targeting and content recommendations. The bet: AI embedded in apps matters more than AI as a standalone product.

Strategy: Platform play. AWS offers every model through Bedrock rather than picking winners. The Anthropic investment ensures access to frontier models while Trainium chips reduce NVIDIA dependence. Amazon's AI is less visible but deeply embedded in logistics, recommendations, and enterprise workflows.

Strategy: Privacy-first, device-centric. Apple bets that on-device AI + privacy differentiation beats cloud-first approaches. Apple Intelligence runs locally where possible, using OpenAI for complex queries. The advantage: 2.2B devices and consumer trust. The risk: capability gap vs. cloud-native competitors.