AI-Assisted Decision Governance Checklist

AI-assisted systems may generate drafts, classifications, summaries, suggestions, or actions. They should be governed as decision-support tools, with clear data limits and human responsibility.

Scope note: This is a vendor-neutral governance checklist. It does not claim that any product offers AI settings, prompts, automation, dispatch, permissions, audit logs, integrations, recommendations, performance, or outcomes.

Define the narrow use case

Write the approved purpose, expected inputs, prohibited inputs, possible outputs, human owner, and immediate stop condition. Do not start with safety, emergency, legal, financial, employment, privacy, health, access, or customer-impacting decisions.

Treat outputs as drafts

An AI output may be incomplete, inaccurate, stale, biased, or unsuitable for the context. A suggestion, classification, summary, priority, or draft is not an approved communication, dispatch decision, customer commitment, price, authorization, completed work, payment, or collected cash.

Require human review before a result is used externally or changes a material record.

Set a strict data boundary

Use only the minimum necessary and authorized data. Do not put production names, contact details, addresses, locations, payment data, personnel data, credentials, tokens, account IDs, internal links, screenshots, logs, recordings, or documents into public examples or unapproved prompts.

Review data permissions, retention, incident handling, vendor terms, and revocation before connecting any system to business data.

Test with fully synthetic scenarios

Situation Expected control
Clear low-risk request Reviewable draft or suggestion
Missing or conflicting information Pause for clarification
Sensitive or urgent request Documented human escalation
Incorrect or harmful output Stop, record, and correct
Unauthorized data or access Restrict, revoke, and review

Keep human accountability

Document who reviews outputs, what evidence is checked, what can be changed, and how a mistake is corrected. A log, status, or system message is not proof that the real-world outcome occurred.

Review regularly

Set a review date for authorization, data minimization, output quality, access, escalation, and incidents. If the process is unclear, unauthorized, inaccurate, or irreversible, pause it until the qualified owner resolves it.

Discussion

Which decision in your team should always remain human-owned even if an AI tool can prepare a draft?