Set the boundary
Clarify approved tools, prohibited information, disclosure expectations and decisions that cannot be delegated to AI.
Lead responsible adoption
AI Training for Managers
Managers need more than prompt tips. They need a practical way to approve use cases, identify risk, coach employees and decide where human review belongs.
The people and work
Built around this team’s responsibilities
- People managers and supervisors
- Department heads introducing AI tools
- Leaders responsible for quality and risk
Role-specific outcomes
01
A framework for approving use cases
02
Questions for reviewing AI-assisted work
03
Coaching language for hesitant employees
04
Practical policy discussion points
What the training addresses
Practice grounded in the work this team owns
Review the work
Use a consistent check for accuracy, source quality, bias, tone, privacy and accountability.
Lead the change
Create safe opportunities to practise without pressuring staff or treating AI use as a hidden productivity contest.
Why this training is different
The workplace challenge behind the session
A manager does not need to approve every prompt. They do need to know which uses are appropriate, what evidence is required, how work will be reviewed and when an employee should stop.
01
Approve a use case
- Situation
- An employee wants AI to draft a recurring report from internal notes.
- In the room
- Managers assess purpose, data, error impact and review ownership.
- Quality check
- The proposal receives a decision with clear conditions.
02
Coach a weak draft
- Situation
- The writing is polished, but evidence and assumptions are missing.
- In the room
- Managers ask for sources, uncertainty and comparison with originals.
- Quality check
- Feedback addresses the work standard, not prompt fluency.
03
Support an uncertain employee
- Situation
- A staff member worries about expectations and mistakes.
- In the room
- Managers define a bounded, low-risk practice task.
- Quality check
- Sound judgment—not speed—is the measure of success.
How the learning progresses
A deliberate path from explanation to accountable use
Select
Choose tasks using risk and value, not novelty.
Set
Define tools, information limits and work standards.
Review
Ask for sources, assumptions and accountable sign-off.
Coach
Support different confidence levels fairly.
Decisions to settle
- What makes a use case low, medium or high risk
- Which decisions remain fully human
- What evidence accompanies AI-assisted work
- How incidents and near misses are reported
Prepare for a useful session
- Bring two proposed team use cases
- Identify existing approval checkpoints
- Review employee guidance
- List questions managers already receive
Continue planning
Choose the next detail your organization needs
Training at your workplace
Train your managers in person.
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