AI Risk Register Template: How to Document and Track AI Risks

Executive Summary

• A risk register is the central document for tracking, managing, and reporting AI risks
• Effective registers capture risk details, assessment scores, treatment plans, and status
• This template provides a ready-to-use format with example entries
• Maintain one register per AI system or one consolidated register with system tags
• Regular review (monthly or quarterly) keeps the register current and actionable
• The register supports [governance committee] reporting and audit requirements
• Document format matters less than consistent use—choose what works for your organization

Risk Register Core Fields

Example Risk Entry

Risk ID:          AI-2024-001
AI System:        Customer Service Chatbot
Category:         Accuracy
Description:      Chatbot provides incorrect information
Likelihood:       3 (Possible)
Impact:           4 (Major)
Risk Score:       12 (High)
Treatment:        Mitigate
Owner:            [Customer Service Director]
Status:           In Progress

Mitigation Actions:
1. Implement confidence scoring | Due: Oct 15 | In Progress
2. Add escalation to human agents | Due: Oct 30 | Complete

Summary Dashboard Template

RISK SUMMARY
━━━━━━━━━━━━
TOTAL RISKS: 12

By Score:
  Critical (20-25):  1
  High (15-19):      3
  Medium (8-14):     5
  Low (1-7):         3

By Status:
  Open:              4
  In Progress:       6
  Closed:            2

Overdue Actions:     2

Review Cadence

Next Steps

Download the template and adapt it to your organization. Start by documenting risks for your most critical AI systems.

Book an AI Readiness Audit with Pertama Partners for help establishing your risk management framework.

Related Reading

• [AI Risk Assessment Framework: A Step-by-Step Guide]
• [10 AI Risks Every Executive Should Understand]
• [How to Report AI Risks to Your Board]

Anatomy of a Production-Grade AI Risk Register

Enterprise risk registers for artificial intelligence deployments require specialized attributes beyond traditional information technology risk documentation. Pertama Partners designed comprehensive risk register templates through governance advisory engagements across banking, insurance, telecommunications, healthcare, and manufacturing organizations in Singapore, Malaysia, Indonesia, and Thailand between March 2025 and February 2026.

Column Architecture. Each register entry should capture fourteen distinct attributes organized into four logical groupings:

Identification Group (Columns One Through Four). Unique risk identifier following organizational taxonomy conventions (e.g., AIR-FIN-2026-017 indicating AI Risk, Finance domain, year, sequence number). Descriptive risk title providing immediate comprehension without requiring detailed description review. Discovery date recording when the risk was initially identified through assessment, incident, audit, or stakeholder escalation. Source category classifying the identification mechanism — proactive assessment, reactive incident analysis, regulatory notification, vendor advisory, or employee whistleblower report.

Assessment Group (Columns Five Through Eight). Likelihood rating using calibrated five-point probability scales anchored to quantitative frequency estimates: Rare (less than five percent annual probability), Unlikely (five to twenty percent), Possible (twenty to fifty percent), Likely (fifty to eighty percent), and Almost Certain (exceeding eighty percent). Impact severity assessment across four consequence dimensions: financial exposure quantified in currency ranges, reputational damage potential categorized by stakeholder visibility, operational disruption scope measured by affected process counts and user populations, and regulatory compliance consequence severity ranging from observation findings through formal enforcement actions.

Mitigation Group (Columns Nine Through Twelve). Current control inventory documenting every existing safeguard with implementation status classification: Fully Implemented, Partially Implemented, Planned, or Not Started. Control effectiveness rating assessed through testing evidence including penetration test results from Burp Suite or OWASP ZAP, bias audit findings from IBM Fairness 360 or Microsoft Fairlearn toolkit evaluations, performance monitoring validation through Evidently or WhyLabs platform outputs, and access control verification through identity management audit trails. Residual risk classification calculating remaining exposure after applied mitigation controls. Planned enhancement actions describing additional controls under development with target completion dates and responsible owner assignments.

Accountability Group (Columns Thirteen and Fourteen). Designated risk owner identified by name, title, department, and contact information rather than generic role references. Review schedule specifying the next scheduled reassessment date and triggering conditions for interim reviews including material operational changes, regulatory updates, incident occurrences, or organizational restructuring events.

Integrating Risk Registers with Broader Governance Ecosystems

Standalone risk registers provide limited organizational value unless systematically connected to complementary governance mechanisms. Pertama Partners recommends three integration pathways ensuring risk documentation influences operational decision-making:

Integration Pathway One — Model Registry Linkage. Connect risk register entries to corresponding model registry records maintained in platforms like MLflow, Weights and Biases, or Neptune.ai. Each deployed model should reference its associated risk entries, enabling governance committees to evaluate aggregate risk exposure across the deployment portfolio during quarterly review sessions.

Integration Pathway Two — Incident Management Connection. Establish bidirectional linkage between risk register entries and incident tracking systems including ServiceNow, Jira Service Management, PagerDuty, or Opsgenie. When incidents materialize from documented risks, the register captures actualization evidence validating initial assessment accuracy. When novel incidents occur without corresponding register entries, the discovery triggers immediate risk documentation and gap analysis procedures.

Integration Pathway Three — Regulatory Compliance Mapping. Cross-reference each risk entry against applicable regulatory requirements from relevant jurisdictions including Singapore's Personal Data Protection Act administered by PDPC, Malaysia's Personal Data Protection Act 2010 enforced by Department of Personal Data Protection, Thailand's PDPA enforced by the Personal Data Protection Committee, Indonesia's PDP Law Number 27 of 2022, and European Union GDPR requirements for organizations with European data subject exposure. This mapping enables compliance teams to demonstrate regulatory awareness during supervisory examinations and audit proceedings.

Practical Next Steps

To put these insights into practice for ai risk register template, consider the following action items:

• Establish a cross-functional governance committee with clear decision-making authority and regular review cadences.
• Document your current governance processes and identify gaps against regulatory requirements in your operating markets.
• Create standardized templates for governance reviews, approval workflows, and compliance documentation.
• Schedule quarterly governance assessments to ensure your framework evolves alongside regulatory and organizational changes.
• Build internal governance capabilities through targeted training programs for stakeholders across different business functions.

Effective governance structures require deliberate investment in organizational alignment, executive accountability, and transparent reporting mechanisms. Without these foundational elements, governance frameworks remain theoretical documents rather than living operational systems.

The distinction between mature and immature governance programs often comes down to enforcement consistency and stakeholder engagement breadth. Organizations that treat governance as an ongoing discipline rather than a checkbox exercise develop significantly more resilient operational capabilities.

Regional regulatory divergence across Southeast Asian markets creates additional governance complexity that multinational organizations must navigate carefully. Jurisdictional differences in enforcement priorities, disclosure requirements, and penalty structures demand locally adapted governance responses.