Decision inputs
Facts that change the policy answer
The working material is event data, account attributes and product questions; the intended result is usage patterns and possible friction points. Recording that pair prevents a vague approval from spreading to other uses.
- 1Task and owner
- Product analyst wants to analyse product usage data. Responsibility for usage patterns and possible friction points stays with a named person or team throughout the request.
- 2Information involved
- Event data, account attributes and product questions. Include attachments and connected sources when deciding the highest information classification.
- 3Tool and account
- An approved company account. A personal login can handle information differently from the company-managed version of the same tool.
- 4Intended result
- The expected result is usage patterns and possible friction points. State whether another person will see it, rely on it or receive an action produced from it.
- 5Consequence if it is wrong
- Small groups and detailed events can reveal identifiable behaviour. Use this consequence to distinguish a routine request from one needing specialist approval.
- 6Human review
- product analytics owner should inspect, change, reject or stop the result. A final glance after an automatic action would not give that owner meaningful control.
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 company can consider a standard route where the exact account is approved, only the minimum customer usage information is used, usage patterns and possible friction points remains within the stated purpose, and product analytics owner reviews it before use.
Approval may be required
The request moves beyond routine handling when the account or data handling is uncertain, small groups and detailed events can reveal identifiable behaviour, or usage patterns and possible friction points reaches people or systems beyond the requester’s authority.
The request may need to stop or change
Do not continue unchanged when restricted information would enter an unapproved service, the output would act before product analytics owner can intervene, or aggregate appropriately and test whether the finding survives alternative explanations cannot be maintained. Consider less information, a controlled account or a non-AI process.
Request checklist
Questions to ask before using the tool
- 01
Will analyse product usage data run inside the approved company environment from start to finish?
- 02
What is the most sensitive element in event data, account attributes and product questions, and does the tool need it?
- 03
Could someone treat usage patterns and possible friction points as final even though it was generated as assistance?
- 04
What evidence will product analytics owner use to accept, correct or reject the result?
- 05
Would another region, audience or frequency activate a different company rule?
Worked request
What the employee should submit
This example supplies decision facts without pasting the underlying material into the approval record.
- requester
- product analyst
- task
- Use AI to analyse product usage data.
- information
- event data, account attributes and product questions
- tool
- An approved company account
- frequency
- Recurring work
- region
- Where the work and affected people are located
- purpose
- Analyse
- impact
- Internal work
- review
- Complete human review
- owner
- product analytics owner
Useful safeguards
Controls that fit this request
- ✓
Aggregate appropriately and test whether the finding survives alternative explanations
- ✓
Document why each part of event data, account attributes and product questions is necessary before making it available to the tool.
- ✓
Keep the use within analyse and run another check if the audience, tool or intended effect changes.
- ✓
Record the request and reviewer without copying unnecessary parts of event data, account attributes and product questions into the audit trail.
Questions people ask
About this AI use
Is using AI to analyse product usage data automatically allowed?
Treat this as a request pattern. The authoritative answer comes from the current company policy and the employee’s completed submission.
What belongs in the employee’s request?
Describe usage patterns and possible friction points, identify event data, account attributes and product questions, name the exact tool and account, explain who will receive or rely on the output, and state how product analytics owner will review it.
How much of the request should the company retain?
Record the request and reviewer without copying unnecessary parts of event data, account attributes and product questions into the audit trail. A classification and controlled reference may be enough when copying event data, account attributes and product questions would create unnecessary risk.