The Strategic Answer to GenAI: Empirical Enterprise Evolution
summary
GenAI demands an enterprise-level strategy: adopt AM3’s three doctrines — empirical control, overall optimization, and evolution focus — use Wily mapping to locate product stages, and run an enterprise backlog to align arenas, teams and sprints. Expect big constraints (compute/energy, data access, training know-how), note the cited 70–95% failure rate of GenAI projects and the $7B 2026 investment estimate, and prioritize data readiness, hidden-dependency discovery, and AI‑enhanced teams that actually ship.
AI-written summary · about
chapters (14)
- 0:00Introduction to talk
- 5:34What is AM3 framework
- 12:47Constraints of GenAI adoption
- 16:40Strategic doctrines for GenAI
- 18:14Empirical control doctrine
- 24:19Anticipating GenAI evolution
- 26:47Wardley mapping for GenAI
- 31:32Asking strategic questions
- 36:48New services vs efficiency
- 39:46Case study: Crumpy and Trias
- 40:53AI agents and development teams
- 42:18AI-enhanced teams future
- 47:01Overall optimization doctrine
- 49:52Closing and Q&A
related talks
01h 06mAI in the Trenches: Engineering Real-World Systems
34mOrganized chaos adopting GenAI at Enterprise
11mOpen source GenAI vs. enterprise GenAI: Navigating the future of AI innovation
34mHow will GenAI impact enterprise data and AI strategy?
49mWhere GenAI projects fail & how can leaders prevent it
29mWhen to Gen AI? A strategic framework for real-world AI adoption
47mCreating a Generative AI Adoption Roadmap
17mGenerative AI Impact on Enterprises