Drive AI Adoption Across Your Team by Treating It Like a Product Problem
Increase AI adoption by segmenting users, identifying barriers, designing enablement loops, and measuring behavior change.
Outcome
A practical AI adoption plan based on user needs, not generic training.
Workflow steps
Segment the team
Identify power users, skeptics, blocked beginners, and people with high-leverage use cases.
Map adoption barriers
Look for trust, access, skill, policy, workflow, and incentive barriers.
Design enablement loops
Create examples, office hours, reusable workflows, and proof points that spread.
Why this workflow matters
AI adoption does not happen because a tool is available. It happens when people see a use case that fits their work and trust the result.
How to run it
Treat adoption like product discovery. Segment users, identify jobs and blockers, ship enablement experiments, and measure behavior change.
What good looks like
Your team should move from scattered experimentation to repeatable, useful AI-assisted workflows.