Through your post into ChatGPT and this is what I got back:

Yes — the safest approach is: increase legitimate, reviewable AI-assisted work, not token volume. Make every interaction defensible if someone audits it.

Good use cases for your role:

1. Troubleshooting documentation

After solving an issue, ask AI to produce:

“Create a short troubleshooting note for this issue: symptoms, root cause, fix, prevention, and validation steps.”

That turns normal troubleshooting into reusable knowledge.

2. PowerShell script hardening

For every script, ask for:

“Review this script for error handling, logging, idempotency, rollback, permissions, and edge cases.”

That is genuinely useful and not fluff.

3. Change management support

Use AI to draft:

• change request descriptions
• implementation plans
• backout plans
• validation steps
• risk/impact statements
• stakeholder communication

Example:

“Turn this technical change into an ITIL-style change request with risk, impact, implementation steps, validation, and rollback.”

4. Root cause and prevention analysis

Your idea is solid. After an error is fixed, ask:

“Explain the likely root cause, contributing factors, how to prevent recurrence, and what monitoring would catch this earlier.”

5. Meeting prep and follow-up

Use it for:

• agenda creation
• decision summaries
• action item cleanup
• executive summaries
• technical-to-business translation

Example:

“Convert these technical notes into a manager-friendly summary with risks, decisions needed, and next steps.”

6. Policy, SOP, and runbook creation

Any recurring admin task can become a runbook:

“Create a runbook for this task including prerequisites, steps, validation, rollback, and escalation points.”

7. Learning and upskilling

For minimal PowerShell coding, ask:

“Explain what this command does line by line, then show a safer production version.”

That is legitimate skill-building.

8. Peer-review simulation

Before sending something to a team or leadership:

“Review this from the perspective of a security engineer, systems admin, and IT manager. Identify gaps or unclear assumptions.”

9. Comparison and decision support

For troubleshooting or tooling:

“Give me three possible causes, how to test each one, and which is most likely based on the evidence.”

10. Personal reusable prompt library

Build prompts you reuse often, such as:

“Act as a senior systems engineer. Review the following issue and provide: likely cause, immediate fix, long-term prevention, validation steps, and documentation-ready summary.”

The key is to make your AI usage produce artifacts: scripts, runbooks, change records, summaries, checklists, validation plans, and documentation. That increases usage while also creating things your manager can look at and say, “That was actually useful.”

Sounds like a good prompt for AI.... plugged your post into ChatGPT and here you go:

Yes — the safest approach is: increase legitimate, reviewable AI-assisted work, not token volume. Make every interaction defensible if someone audits it.

Good use cases for your role:

1. Troubleshooting documentation

After solving an issue, ask AI to produce:

That turns normal troubleshooting into reusable knowledge.

2. PowerShell script hardening

For every script, ask for:

That is genuinely useful and not fluff.

3. Change management support

Use AI to draft:

• change request descriptions
• implementation plans
• backout plans
• validation steps
• risk/impact statements
• stakeholder communication

Example:

4. Root cause and prevention analysis

Your idea is solid. After an error is fixed, ask:

5. Meeting prep and follow-up

Use it for:

• agenda creation
• decision summaries
• action item cleanup
• executive summaries
• technical-to-business translation

Example:

6. Policy, SOP, and runbook creation

Any recurring admin task can become a runbook:

7. Learning and upskilling

For minimal PowerShell coding, ask:

That is legitimate skill-building.

8. Peer-review simulation

Before sending something to a team or leadership:

9. Comparison and decision support

For troubleshooting or tooling:

10. Personal reusable prompt library

Build prompts you reuse often, such as:

The key is to make your AI usage produce artifacts: scripts, runbooks, change records, summaries, checklists, validation plans, and documentation. That increases usage while also creating things your manager can look at and say, “That was actually useful.”