SECTION 1 - CONDITIONS: PRINCIPLES FOR LEAN + AI Chapter 1 - AI Does Not Fix Lean - It Reveals It Chapter 2 - Lean Must Lead - AI Must Follow Chapter 3 - Respect for People Is the Constraint Chapter 4 - Learning Speed - Not Efficiency - Is the Advantage Chapter 5 - Visibility Without Judgment Is Dangerous Chapter 6 - Gemba Cannot Be Digitized Chapter 7 - Small Experiments Build Trust - Big Launches Destroy It Chapter 8 - Capability, Not Tools, Determines the Outcome Chapter 9 - Lean Civilizes AI SECTION 2 - EVIDENCE: VOICES FROM THE FIELD Introduction: Why Voices Matter Expert–Question Map Chapter 10 - The Premise: Why Lean + AI, and Why Now Chapter 11 - Real-World Application: Where AI Meets Continuous Improvement Chapter 12 - Hopes, Risks, and Lessons Learned Chapter 13 – Change Management, Adoption, and Trust Chapter 14 – Practice and Process: Gemba, PDCA, and Digital Tools Chapter 15 – Foundations and Definitions Chapter 16 – Strategy, Leadership, and the Future Enterprise SECTION 3 - PRACTICE: LEADING LEAN + AI Chapter 17 - Where Leaders Go Wrong – and What to Do Instead Chapter 18 - What Must Be Stabilized Before Introducing AI Chapter 19 – How to Experiment with AI Without Damaging Learning Chapter 20 – Integrating AI in to Daily Management Without Losing Control Chapter 21 – Knowing When – and When Not – to Scale AI Chapter 22 - Sustaining Lean + AI Over Time Closing A Final Word on Co-Intelligence Expert Index