AI Risk Register: Template, Guide & Automation

What Is an AI Risk Register?

An AI risk register is a living document (or software-managed database) that records every AI system an organization operates, the risks each system poses, the controls in place to mitigate those risks, and the current remediation status of any identified issues.

Unlike a generic IT risk register, an AI risk register must capture AI-specific attributes: training data sources, model type, decision type (advisory vs. autonomous), affected populations, and the regulatory frameworks that apply to each system.

What Goes in an AI Risk Register?

A well-structured AI risk register entry should capture at minimum:

• System name, vendor, and version
• Business purpose and department owner
• Decision type: advisory, augmented, or autonomous
• Data inputs and training data sources
• Affected populations and potential for disparate impact
• Risk tier: Low, Moderate, or High; binary HSAI determination for Texas governmental entities (SB 1964)
• Applicable regulatory frameworks
• Assigned controls and completion status
• Outstanding issues and remediation deadlines
• Last review date and next scheduled review
• Incident history
• Executive certification status

AI Risk Register Requirements by Regulation

Several major AI regulations explicitly require organizations to maintain an AI risk register or equivalent system inventory.

• SB 1964 / 1 TAC Chapter 219 (Texas) — requires Texas governmental entities to inventory their AI systems, make binary Heightened Scrutiny AI (HSAI) determinations, and maintain § 219.22 risk assessment records. For private-sector organizations under TRAIGA, a documented AI risk register is best practice rather than a statutory mandate.
• NIST AI RMF — the MAP function requires a comprehensive inventory of organizational AI systems with associated risk characteristics.
• ISO/IEC 42001:2023 — Clause 6.1 requires organizations to identify AI-related risks and opportunities and document them systematically.
• Colorado Artificial Intelligence Act — Section 6-1-1703 requires high-risk AI deployers to maintain documentation of AI system purpose, data used, and risk mitigation measures.

Automate Your AI Risk Register with TRAIGA

Building and maintaining an AI risk register manually in spreadsheets is error-prone and fails under audit. TRAIGA automates the entire risk register workflow: add an AI system, answer a structured questionnaire, and the platform auto-scores risk, generates controls, and tracks remediation status in real time.

Every field is audit-logged with user, timestamp, and reason. Export to PDF or CSV for board packs, regulator requests, or external audit submissions.

Step by step

How to get it done

1. 1

   Inventory all AI systems

   Conduct a comprehensive discovery exercise to identify every AI system the organization develops, operates, or procures from third parties.

2. 2

   Define risk criteria

   Establish the risk dimensions you will assess for each system: decision impact, data sensitivity, affected populations, regulatory applicability, and model opacity.

3. 3

   Classify each system's risk tier

   Apply your risk criteria to classify each AI system as Low, Moderate, or High risk; Texas governmental entities should also record the binary SB 1964 HSAI determination for each system.

4. 4

   Assign controls to each system

   Map a set of governance controls to each system based on its risk tier and applicable regulations. Document control owners and target completion dates.

5. 5

   Establish a review cadence

   Schedule periodic reviews — at minimum annually, and immediately after any significant change to the system, its data, or the regulatory environment.

6. 6

   Automate with TRAIGA

   Move from manual spreadsheets to TRAIGA's automated AI risk register — auto-scoring, control tracking, audit logs, and one-click board-ready reports.

Frequently asked questions

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