User Training
This playbook covers training for end users of an AI solution: materials, formats, adoption metrics, and feedback. It is used before production launch and during the first weeks of operations.
Goal
Users should understand:
- what task the AI solution solves;
- where it fits into the process;
- where AI responsibility ends and human responsibility begins;
- which data can be used;
- how to check the result;
- where to report errors and improvement ideas.
Materials
Minimum package:
- quick-start guide;
- main usage scenario;
- allowed and prohibited data;
- good and bad examples;
- result-check checklist;
- FAQ;
- support channel;
- feedback form.
Formats
| Format | When to use |
|---|---|
| 30-45 minute demo | Before first launch for the main group |
| Practical session | For daily users |
| Video or guide | Scaling and onboarding |
| Office hours | First weeks after launch |
| Error review | When repeated quality or usage issues appear |
Launch sequence
- Define target user groups.
- Prepare materials and real process examples.
- Run training.
- Collect questions and update FAQ.
- Open the support channel.
- Track adoption and quality of use.
- Run a short retrospective after 2-4 weeks.
Adoption metrics
- active users;
- share of target audience using the solution;
- usage frequency;
- successful scenario completion rate;
- support requests;
- repeated error reasons;
- perceived usefulness;
- target business metric change.