Branching scenario · Hand-coded HTML
Leading AI Adoption
A branching scenario where managers choose an AI pilot, plan it and lead their team through it, balancing team trust against progress.
The challenge
Managers were told to "adopt AI" with no guidance on where to start or how to handle a worried team. Slide-based change-management training hadn't changed behaviour, because the hard part is the conversations, not the theory.
My approach
- One quarter in a manager's life, told through eleven scenes where choices change what happens next: a bad answer in the huddle triggers a private worried message, and a vague pilot plan produces vague results later.
- Two live meters, team trust and pilot progress, so learners feel the trade-off between moving fast and bringing people with them.
- Four endings, from "AI champion" to "Stalled", driven by the meters rather than a single right path.
- An opportunity matrix built into the workflow decision, and a printable conversation guide for real team meetings.
Objectives and how each is assessed
Seven decisions are scored 2, 1 or 0. Consequence scenes change the meters but aren't scored, so recovering from a mistake is possible but not free.
| Learning objective | Assessment |
|---|---|
| Assess which team workflows are good candidates for AI. | 2 scored decisions: choose the first pilot from a volume and risk matrix, and pick the next workflow |
| Plan a small, low-risk pilot with clear success measures. | 2 scored decisions: write the pilot plan, then act on its results |
| Address team concerns about job impact. | 3 scored conversations; pass mark 10 of 14, with the learner's path and a model answer shown at the end |
Results and reflection
Add pilot results, reviewer quotes or what you would do differently next time.
Design artefacts
- Manager conversation guide (printable)
- Branching map and storyboard (available on request)