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Practical AI / 2026 Essentials

A Simple AI Use Policy Your Team Can Follow

Produce and test a one-page operational AI policy with explicit approved tools, permitted data, review ownership and an incident route.

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Compiled for Sorlavit Kim · Published · Updated · 3 min read

Practical guide · คู่มือลงมือทำ

Download worksheet · ดาวน์โหลดขั้นตอน

Detailed practical guide

Prepare your workspace and inputs

Create ai-use-policy.md and a separate ten-row decision sheet. Use fictional employees and ticket text; do not distribute a policy as approved until its actual organizational owner accepts it.

Platform context: Document editor or plain text; a fictional support desk, a named policy owner and ten synthetic ticket examples. No external AI account is required.

Scenario to reproduce or investigate

Staff know they may use AI but disagree about whether ticket text, personal information or generated replies may be sent to a tool or customer. The policy needs observable decisions rather than a general instruction to be careful.

Evidence to record in your worksheet
  • Actual target and platform release
  • Exact inputs or substituted values
  • Baseline result
  • Per-step expected and observed output
  • Failure encountered and corrective action
  • Final acceptance and recovery state
  1. Fill the working policy template

    Replace every bracketed field with a real organizational choice or mark it unresolved. Keep the scope to a support-draft workflow so the first policy can be tested. Approval for drafting must not imply approval for autonomous sending or system changes.

    Command, configuration or input

    # AI use policy — support draft workflow
    Owner: [role and contact]
    Effective date / next review: [dates]
    Approved service and account: [service, tenant and approved access route]
    Allowed task: draft a reply from sanitized, approved ticket facts.
    Allowed input: error category, supported product and sanitized symptoms.
    Prohibited input: passwords, tokens, private keys and unnecessary personal data.
    Source rule: use the current approved support procedure; label missing facts unknown.
    Review rule: [support reviewer] verifies facts and recipients before sending.
    Action boundary: this workflow may draft; it may not send or change a system.
    Unapproved tool: stop and contact [tool owner] before uploading data.
    Mistaken disclosure: stop the workflow, preserve the event reference and contact [incident route].
    Records: keep [approved prompt/source version and review decision] for [agreed retention].
    Exception owner and expiry: [role, documented reason and review date].
    Expected result · ผลที่ควรเห็น

    The policy identifies one service, one permitted workflow, prohibited data, an accountable reviewer and an actionable incident route.

    If it fails · เมื่อไม่ผ่าน

    If an owner, retention or approved service remains unresolved, keep that workflow unavailable rather than treating a blank field as permission.

  2. Test ten concrete staff decisions

    Build a decision sheet containing four allowed sanitized tickets, three tickets needing redaction, two tickets containing a fake secret and one request to use an unapproved tool. Have two readers classify the same sheet independently before comparing answers.

    Command, configuration or input

    Case | tool approved? | data allowed? | allow / redact / stop | reviewer | policy clause
    1 | yes | sanitized error | allow | support reviewer | allowed input
    5 | yes | customer phone not needed | redact | support reviewer | prohibited input
    8 | yes | fake API token | stop | incident route if already uploaded | prohibited input
    10 | no | sanitized text | stop | tool owner | unapproved tool
    Expected result · ผลที่ควรเห็น

    All ten cases have a policy clause and responsible role. Reader disagreements become specific policy changes, not informal exceptions.

    If it fails · เมื่อไม่ผ่าน

    If one reader interprets drafting approval as sending approval, strengthen the action boundary and repeat that case with both readers.

  3. Rehearse a mistaken disclosure and publish the accepted revision

    Use a fake token and a mock event reference to rehearse reporting. Verify the incident route reaches an active role through the organization’s approved test method. Record the policy owner’s acceptance, revision and review date, then publish through the normal staff channel with the decision sheet for training.

    Command, configuration or input

    Acceptance record: revision | owner | ten-case result | reporting rehearsal | effective date | next review
    Expected result · ผลที่ควรเห็น

    Staff can find the current policy, classify the training cases and identify where to report a mistake.

    If it fails · เมื่อไม่ผ่าน

    If no owner can receive a report or revoke the tool integration, fix that operational gap before treating the policy as enforceable.

Check the result before marking this passed

The policy contains no unresolved permission fields, both readers reach the intended decision on all ten cases after corrections, and the reporting rehearsal has a recorded recipient and outcome.

Record the observed result and evidence location in the downloaded worksheet. Mark unresolved or untested conditions explicitly.

Recovery and cleanup

Retain the prior policy revision and training decisions. Revoke publication of an unaccepted draft and restore the last accepted version if the new wording grants unintended permission.

Apply to actual work and known limits

Adapt the draft with the actual data owner, tool owner and review process. A written policy does not replace tenant settings, technical access controls or the organization’s required legal review.

Authored against the cited documentation. Execution on the stated vendor product or physical equipment remains to be verified.

Background, explanations and original notes

Prepare the exact environment

Create ai-use-policy.md and a separate ten-row decision sheet. Use fictional employees and ticket text; do not distribute a policy as approved until its actual organizational owner accepts it.

Fill the working policy template

Replace every bracketed field with a real organizational choice or mark it unresolved. Keep the scope to a support-draft workflow so the first policy can be tested. Approval for drafting must not imply approval for autonomous sending or system changes.

# AI use policy — support draft workflow
Owner: [role and contact]
Effective date / next review: [dates]
Approved service and account: [service, tenant and approved access route]
Allowed task: draft a reply from sanitized, approved ticket facts.
Allowed input: error category, supported product and sanitized symptoms.
Prohibited input: passwords, tokens, private keys and unnecessary personal data.
Source rule: use the current approved support procedure; label missing facts unknown.
Review rule: [support reviewer] verifies facts and recipients before sending.
Action boundary: this workflow may draft; it may not send or change a system.
Unapproved tool: stop and contact [tool owner] before uploading data.
Mistaken disclosure: stop the workflow, preserve the event reference and contact [incident route].
Records: keep [approved prompt/source version and review decision] for [agreed retention].
Exception owner and expiry: [role, documented reason and review date].

Test ten concrete staff decisions

Build a decision sheet containing four allowed sanitized tickets, three tickets needing redaction, two tickets containing a fake secret and one request to use an unapproved tool. Have two readers classify the same sheet independently before comparing answers.

Case | tool approved? | data allowed? | allow / redact / stop | reviewer | policy clause
1 | yes | sanitized error | allow | support reviewer | allowed input
5 | yes | customer phone not needed | redact | support reviewer | prohibited input
8 | yes | fake API token | stop | incident route if already uploaded | prohibited input
10 | no | sanitized text | stop | tool owner | unapproved tool

Rehearse a mistaken disclosure and publish the accepted revision

Use a fake token and a mock event reference to rehearse reporting. Verify the incident route reaches an active role through the organization’s approved test method. Record the policy owner’s acceptance, revision and review date, then publish through the normal staff channel with the decision sheet for training.

Acceptance record: revision | owner | ten-case result | reporting rehearsal | effective date | next review

Acceptance check

The policy contains no unresolved permission fields, both readers reach the intended decision on all ten cases after corrections, and the reporting rehearsal has a recorded recipient and outcome.

Recovery and cleanup

Retain the prior policy revision and training decisions. Revoke publication of an unaccepted draft and restore the last accepted version if the new wording grants unintended permission.

Apply to actual work and known limits

Adapt the draft with the actual data owner, tool owner and review process. A written policy does not replace tenant settings, technical access controls or the organization’s required legal review.

Source & further reading

NIST AI Risk Management Framework

Independently written summary reviewed on 2026-11-04. The example illustrates a possible application; it is not a client case study.

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