AI Adoption & Change Management

AI adoption course, AI change management, how to drive AI adoption at work, AI adoption playbook, building AI champions, measuring AI adoption, AI rollout strategy, scale AI across an organization, AI adoption metrics, change management for AI

practitioner

en

• Run a stage-by-stage AI rollout from pilot to org-wide scale using the five adoption stages
• Diagnose and respond to the resistance patterns that stall AI rollouts
• Recruit, enable, and sustain a network of AI champions with toolkits and rotation models
• Prevent champion burnout while keeping grassroots momentum
• Pick the four adoption metrics that drive behavior and cut the four vanity metrics that mislead
• Use leading indicators to decide when an AI rollout has actually succeeded
• Embed AI into daily team rituals so usage holds after the launch push

• Url: https://aiacademy.anthropos.work/chapters/adoption-ai-intro/ · AI Adoption & Change Management · Position: 1 · Why rollouts fail, how to make AI stick, and the operational playbook from pilot to scale
• Url: https://aiacademy.anthropos.work/chapters/adoption-playbook/ · The AI Adoption Playbook · Position: 2 · Stage-by-stage operational model from pilot to scale — the five adoption stages, resistance patterns, and the grassroots tactics that make AI stick
• Url: https://aiacademy.anthropos.work/chapters/adoption-champions/ · Building AI Champions · Position: 3 · Find, enable, and sustain the grassroots layer — champion profiles, toolkits, burnout prevention, and rotation models
• Url: https://aiacademy.anthropos.work/chapters/adoption-measuring/ · Measuring AI Adoption · Position: 4 · Leading indicators, behavior-driving metrics, and when to declare success — the four metrics that matter and the four vanity metrics to kill

• Run a stage-by-stage AI rollout from pilot to org-wide scale using the five adoption stages
• Diagnose and respond to the resistance patterns that stall AI rollouts
• Recruit, enable, and sustain a network of AI champions with toolkits and rotation models
• Prevent champion burnout while keeping grassroots momentum
• Pick the four adoption metrics that drive behavior and cut the four vanity metrics that mislead
• Use leading indicators to decide when an AI rollout has actually succeeded
• Embed AI into daily team rituals so usage holds after the launch push

Course Mode: online · Course Workload: PT79M · Mode: online