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Day 1 — Understand
- Mapping AI in 2026: where the disruption lies, where the noise is
- Executive demonstrations: GPT, Claude, Gemini, Mistral compared
- The economics of AI: cost of the token, cost of the model, cost of error
- Strategic reading: 12 real-world case studies (banking, retail, industry, services)