Change Management for AI

Change Management for AI

Step 1 of 8

staff400

The same tool goes to the same 400 people four times. Only what happens around the launch changes.

The Idea

Tools do not adopt themselves. Resistance usually comes from fear for jobs, distrust of the output, or no time to learn. What moves the curve: honest communication about what changes, training on people's own tasks, a champion in every team, small experiments where failing is safe, and incentives that count outcomes rather than logins.

Real-World Example

A gym that hands out free memberships in January is packed for two weeks. The gyms that keep members pair the card with an intro session, a workout buddy and a goal people actually track.

The Tradeoff

Training and champions take weeks before usage shows, and a mandate looks faster on a dashboard. It is not: usage nobody wants decays the moment nobody checks. Measure weekly active use and outcomes, not sign-ups.

Your turn

Put the steps in the right order.

1. 1Train people on their own real tasks↑↓
2. 2Run small team experiments and share what worked↑↓
3. 3Explain what changes for roles and on what timeline↑↓
4. 4Measure outcomes and credit time saved in team goals↑↓

Check order

Mini quiz

1 / 3

Weekly usage jumped to 59% after a mandate, then fell to 32%. What does that pattern show?

• AThe tool is broken
• BCompliance without adoption: the concerns were never addressed
• CThe training was too long
• DThe rollout was too slow