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AI Governance Checklist for Project Managers

A 25-item governance checklist for project managers: authorization, risk documentation, decision logging, output review, and audit readiness. Free AI Governance Starter Kit download.

AI Governance for Project Managers

AI Governance Checklist for Project Managers

Most PMs responsible for AI systems cannot answer five questions an auditor would ask. This 25-item checklist makes them answerable.

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Free PDF  ·  Built for PMs and PMO leaders responsible for AI-enabled work

For project managersFor PMO leadersFor inherited AI systemsFor audit readiness
AI Governance Accountability Checklist Sprint Review CHECK ITEM STATUS OWNER 1 Authorization documented — named approver on record DONE PM 2 Risk register active — AI-specific rows and owners DONE PM 3 Decision log in use — significant decisions recorded GAP — 4 Output review standard — customer-facing AI defined PARTIAL TL 5 Audit readiness verified — escalation path documented GAP — 3 gaps found — use the checklist to assign owners and close them
What This Helps You Do
Find authorization gaps before an auditor does
Know exactly which of the 25 items are missing before a compliance review forces the question.
Assign ownership to every gap
Each gap gets a named owner and a deadline, not just a note in a meeting.
Run a consistent quarterly review
A structured framework that does not start from scratch each quarter.
Build a defensible audit trail
Documented governance creates evidence that accountability was taken seriously.
Direct Answer

AI Governance Checklist for Project Managers

The AI Governance Checklist for Project Managers is a 25-item checklist that confirms AI systems have the documentation, approvals, and oversight structures in place before and during project delivery. It covers five governance areas: authorization, risk documentation, decision logging, output review, and audit readiness. Use it at each project stage gate to stay ahead of audit and compliance questions.

AI accountability comes down to five questions every PM should be able to answer: Who authorized this system? What risks have been formally assessed? What significant decisions have been logged, and by whom? What output review process is in place? What is the escalation path if something goes wrong?

Most PMs discover their governance gaps when something goes wrong — an audit, a customer complaint, a compliance review — not before. This 25-item checklist is designed to surface those gaps first.

Work through each section with your team. Mark each item Done, Partial, or Gap. Assign an owner and a deadline to every Gap. Review quarterly and whenever your AI system changes significantly.

Checklist Preview — Sections 1 & 2 of 5

25-Item AI Governance Checklist

Section 1: Authorization and Ownership — 5 items
1.1The AI system has a documented owner — a named person with accountability for its outputs and decisions.
1.2The original authorization to deploy or use this system is documented — who approved it, when, and on what basis.
1.3Any significant change to the system has been authorized and logged (model version, data source, use case expansion).
1.4You know what data the system processes and who authorized that data to be used with it.
1.5If accountability transferred to you, that handoff is documented — including what was known and unknown at the time.
Section 2: Risk Documentation — 5 items
2.1AI-specific risks are documented in a risk register — not just standard project risks.
2.2Known failure modes have been identified : hallucination, model drift, data quality degradation, vendor instability.
2.3Privacy and data handling risks are assessed and documented .
2.4Each risk has an owner and a mitigation plan .
2.5The risk register has been reviewed within the last 90 days .
Gated content

Section 3: Decision Logging · Section 4: Output Review Standards · Section 5: Audit Readiness — 13 remaining items are in the download below.

Get the Complete 25-Item Checklist

Sections 3–5 (Decision Logging, Output Review Standards, and Audit Readiness — 13 remaining items) are in the AI Governance Starter Kit.

  • AI Governance Checklist — 25 items across 5 sections
  • AI Risk Register Template — 5 AI-specific risk categories
  • AI Decision Log Template — 5-field entry structure
  • AI Governance Framework Template — 5-section policy structure
  • AI Risk Assessment Checklist — 20 items, 4 categories

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The accountability structure behind this checklist is drawn from Authorizing the Machine — a practical guide to AI accountability for project managers. Coming soon.

Frequently Asked Questions

What should an AI governance checklist for project managers include?

An AI governance checklist for project managers should include authorization controls (who approved the AI system), risk documentation (AI-specific risks in the register), decision logging (records of who decided what and why), output review standards (who checks AI outputs before use), and audit readiness (can you reconstruct the governance trail if asked?).

How is an AI governance checklist different from a standard project checklist?

Standard project checklists don't cover AI-specific risks like hallucination, model drift, vendor dependency, or data provenance. An AI governance checklist adds these dimensions alongside standard governance items.

When should a project manager use an AI governance checklist?

At project initiation (before approving AI tool use), at each stage gate (to confirm governance is current), and before project closeout (to confirm documentation is complete and retrievable for audit).

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