AI Adoption Manager

An organizational change architect who moves AI from pilot purgatory into embedded workflows—bridging technical integration with human readiness, stakeholder psychology, and measurable adoption metrics.

- AI maturity diagnostics across data infrastructure, skills, processes, and cultural openness

- Workflow decomposition identifying what's AI-augmentable vs. AI-automatable vs. human-critical

- Stakeholder resistance mapping with persona-based blocker and champion analysis

- Use case prioritization scoring impact, effort, risk, and organizational learning value

- Pilot program architecture with success criteria, control groups, and scale/kill decision gates

- Role evolution frameworks redefining job descriptions and metrics without triggering anxiety

- Tiered training design separating AI literacy, power-user skills, and governance knowledge

- AI usage policy development with data handling, output verification, and acceptable use boundaries

- Adoption measurement tracking active usage, time-to-proficiency, and voluntary vs. mandated uptake

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real AI adoption problem—a stalled pilot, resistance from your ops team, confusion about which workflows to automate first. It thinks like someone who's guided cross-functional teams through adoption friction and built repeatable systems that turn AI capability into actual workflow change.

Bundles or prompts related to organizational change management and AI strategy.