AI Governance Checklist: 12 Steps to a Compliant Program

Why You Need an AI Governance Checklist

AI governance programs fail for two reasons: scope creep (trying to do everything at once) and scope narrowing (treating governance as a one-time audit exercise). A checklist solves both problems by breaking the work into discrete, sequenced steps with clear regulatory mapping.

This checklist is designed for compliance teams, Chief AI Officers, and legal counsel who need to stand up or audit an AI governance program aligned to multiple regulatory frameworks.

Foundation Steps (Steps 1–3)

Every AI governance program starts with the same three foundational activities, regardless of organization size or regulatory exposure.

• Step 1: Appoint AI Governance Leadership — Designate a Chief AI Officer or AI governance committee with defined authority, reporting line, and accountability for AI governance outcomes.
• Step 2: Inventory All AI Systems — Conduct a comprehensive discovery to identify every AI system the organization develops, operates, or procures from third parties. This becomes your AI risk register.
• Step 3: Adopt an AI Governance Policy — Draft and ratify a board-approved AI governance policy that sets principles, scope, roles, and accountability for AI use across the organization.

Risk Management Steps (Steps 4–6)

Once the foundation is in place, the next phase establishes the risk management infrastructure.

• Step 4: Classify AI Systems by Risk Tier — Apply a risk classification framework (SB 1964 HSAI determination or NIST AI RMF) to every AI system in the inventory.
• Step 5: Conduct Algorithmic Impact Assessments — For high-risk systems, perform a structured AIA covering data inputs, decision impact, affected populations, and disparate impact analysis.
• Step 6: Assign and Track Controls — Map a control set to each AI system based on its risk tier and applicable regulations, then assign owners and track completion.

Transparency & Monitoring Steps (Steps 7–9)

Steps 7–9 establish the operational mechanisms that make governance continuous rather than a point-in-time exercise.

• Step 7: Implement Consumer Disclosures — For AI systems that affect external stakeholders, implement the disclosures supporting Texas SB 1188 (§ 183.005(b)), TRAIGA § 552.051 (government agencies), SB 1964 § 2054.711 (governmental entities), and applicable state laws.
• Step 8: Establish an AI Incident Response Process — Define how the organization will detect, investigate, remediate, and document AI-related incidents. Not a TRAIGA mandate, but documented incident response is best practice and strong safe-harbor evidence under TRAIGA § 552.105(e).
• Step 9: Set Up Ongoing Monitoring — Implement technical monitoring for model drift, accuracy degradation, and anomalous outputs. Schedule periodic human reviews for high-risk systems.

Board, Executive & Third-Party Steps (Steps 10–12)

The final three steps institutionalize governance at the leadership and supply chain levels.

• Step 10: Establish Board AI Governance Reporting — Implement a quarterly board reporting cadence covering the AI system inventory, risk posture, incident summary, and control completion rate.
• Step 11: Train Employees — Provide role-based AI governance training to all staff who interact with AI systems in decision-making, with documented completion records.
• Step 12: Manage Third-Party AI Vendors — Conduct due diligence on AI vendors, include TRAIGA compliance requirements in contracts, and monitor vendor compliance annually.

Step by step

How to get it done

1. 1

   Appoint AI Governance Leadership

   Designate a Chief AI Officer or AI governance committee with defined authority and accountability.

2. 2

   Inventory All AI Systems

   Conduct a comprehensive AI system discovery exercise and create your AI risk register.

3. 3

   Adopt an AI Governance Policy

   Draft and ratify a board-approved AI governance policy covering principles, scope, roles, and accountability.

4. 4

   Classify AI Systems by Risk Tier

   Apply a risk classification framework to every AI system in the inventory.

5. 5

   Conduct Algorithmic Impact Assessments

   For high-risk systems, perform a structured AIA covering data inputs, decision impact, and disparate impact.

6. 6

   Assign and Track Controls

   Map a control set to each AI system based on its risk tier and applicable regulations.

Frequently asked questions

Related resources