Decision inputs
Facts that change the policy answer
Within learning and training, this request uses learning objective, workplace context and risk boundaries to produce a realistic practice scenario. Both belong in the submission before any policy route is trusted.
- 1Task and owner
- Learning designer wants to create a role-play training scenario. Responsibility for a realistic practice scenario stays with a named person or team throughout the request.
- 2Information involved
- Learning objective, workplace context and risk boundaries. Look beyond pasted text: files, integrations and retrieval connections can expose the same material.
- 3Tool and account
- An approved company account. Confirm the approved account, retention setting and any connected service before the request begins.
- 4Intended result
- The expected result is a realistic practice scenario. Its destination matters: private working material creates a different consequence from a sent, published or automated result.
- 5Consequence if it is wrong
- A generated example can reproduce a real confidential case or harmful stereotype. This is the fact most likely to move the request from routine handling into review.
- 6Human review
- subject-matter and inclusion owners should inspect, change, reject or stop the result. Make the review happen before reliance and give the reviewer a real way to stop the work.
Possible policy routes
The task name alone cannot decide it.
A published workplace policy can return different answers for the same task. These are the practical branches worth encoding.
A routine policy route may be possible
The least restrictive path starts only after the exact account is approved, only the minimum internal information is used, a realistic practice scenario remains within the stated purpose, and subject-matter and inclusion owners reviews it before use.
Approval may be required
A named reviewer should take over when the account or data handling is uncertain, a generated example can reproduce a real confidential case or harmful stereotype, or a realistic practice scenario reaches people or systems beyond the requester’s authority.
The request may need to stop or change
The policy may require another method where restricted information would enter an unapproved service, the output would act before subject-matter and inclusion owners can intervene, or use fictional facts and review representation and learning purpose cannot be maintained. Consider less information, a controlled account or a non-AI process.
Request checklist
Questions to ask before using the tool
- 01
Does the selected account retain or reuse anything supplied while trying to create a role-play training scenario?
- 02
Could learning objective, workplace context and risk boundaries be reduced to a short de-identified extract?
- 03
Will a realistic practice scenario remain working material, reach another person or make another system act?
- 04
Can subject-matter and inclusion owners inspect the complete result and its source before reliance?
- 05
Is this genuinely one request, or will repeated use turn it into an embedded process?
Worked request
What the employee should submit
This example supplies decision facts without pasting the underlying material into the approval record.
- requester
- learning designer
- task
- Use AI to create a role-play training scenario.
- information
- learning objective, workplace context and risk boundaries
- tool
- An approved company account
- frequency
- Recurring work
- region
- Where the work and affected people are located
- purpose
- Draft or analyse
- impact
- Employee training
- review
- Complete human review
- owner
- subject-matter and inclusion owners
Useful safeguards
Controls that fit this request
- ✓
Use fictional facts and review representation and learning purpose
- ✓
Keep whole files, mailboxes and datasets out of the prompt when a short part of learning objective, workplace context and risk boundaries is enough.
- ✓
Keep the use within draft or analyse and run another check if the audience, tool or intended effect changes.
- ✓
Keep the submitted facts, subject-matter and inclusion owners’s decision and the exact published policy version.
Questions people ask
About this AI use
Is using AI to create a role-play training scenario automatically allowed?
Treat this as a request pattern. The authoritative answer comes from the current company policy and the employee’s completed submission.
What does the policy need to know about this use?
Describe a realistic practice scenario, identify learning objective, workplace context and risk boundaries, name the exact tool and account, explain who will receive or rely on the output, and state how subject-matter and inclusion owners will review it.
What belongs in the completed policy record?
Keep the submitted facts, subject-matter and inclusion owners’s decision and the exact published policy version. A classification and controlled reference may be enough when copying learning objective, workplace context and risk boundaries would create unnecessary risk.