Leading Change When AI Arrives
Lead a team through AI adoption with honesty, involvement and measures that mean something
A taste of a lesson
Leadership wants a dashboard of how often each person uses the AI tool. Is that a good way to drive adoption?
It is a risky one. Per person usage counts tend to produce performative use, people running the tool to look busy, and they can damage trust, especially if staff were not told they would be monitored. Monitoring rules also vary by country, so HR should be involved. Suggest instead measuring a few specific tasks: turnaround, error rates and how often outputs need rework, compared with before. Which task in your team would make a fair before and after comparison?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Explain the purpose of an AI change in plain, honest language
- Map affected groups with their likely gains, losses and concerns
- Design a pilot with feedback loops that lead to visible changes
- Choose adoption measures that reflect value rather than usage
- Handle resistant conversations by treating objections as information
Lesson plan
- 1 Why This Change, Why Now Write a short, honest explanation of the problem the change solves and what is still undecided. Start
- 2 Mapping Who Is Affected Build a stakeholder map showing what each group gains, loses and fears. Start
- 3 Starting With a Pilot Design a pilot with the right mix of people, real tasks and permission to report failure. Start
- 4 Feedback That Changes Things Set up a feedback loop where issues are collected, acted on and the results shared. Start
- 5 Measuring Without Distorting Choose measures that show whether work improved, without encouraging pointless use. Start
- 6 Difficult Conversations Practise responding to fear, anger and quiet refusal with honesty and respect. Start
Try asking
About this tutor
For managers, team leads and project sponsors responsible for bringing AI tools or AI assisted processes into their teams. The lessons cover explaining why the change is happening, mapping who is affected and how, acknowledging real losses as well as gains, starting with a pilot group, setting up feedback that leads to changes, measuring adoption without confusing usage with value, and treating resistance as information. You work on your own change plan with role plays of difficult conversations. This tutor is about leading people through change, not about choosing tools or training content, which other tutors cover.
Reviews
4.7
3 ratingsSample
- Aisha K.Sample
Helped me push back on a usage target with something better. The stakeholder map was useful. A little repetitive on honesty, though it was the point I most needed.
- Tobias M.Sample
The role play where the tutor played a senior colleague who felt replaced was close to my real situation. I went into the real conversation much calmer and actually listened.
- Bruno C.Sample
Writing down what was still undecided felt wrong at first, but my team trusted the announcement more because of it.
About the teacher
The people side of AI at work: change, training, culture and fair practice
9 tutors 407 lessons taught Sample
I teach managers and people teams how to bring AI into a workplace without losing trust. My work background is in people operations and internal communications, so most of my time has gone into the human questions: who feels threatened, who gets credit, what good work looks like now and how to train people who are busy and sceptical. I...
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