AI risk management and governance, so aligning your risk management policy means integrating AI-specific considerations alongside your existing risk framework. Here’s a structured approach:
1. Understand ISO 42001 Scope and Requirements
- ISO 42001 sets standards for AI governance, risk management, and compliance across the AI lifecycle.
- Key areas include:
- Risk identification and assessment for AI systems.
- Mitigation strategies for bias, errors, security, and ethical concerns.
- Transparency, explainability, and accountability of AI models.
- Compliance with legal and regulatory requirements (GDPR, EU AI Act, etc.).
2. Map Your Current Risk Policy
- Identify where your existing policy addresses:
- Risk assessment methodology
- Roles and responsibilities
- Monitoring and reporting
- Incident response and corrective actions
- Note gaps related to AI-specific risks, such as algorithmic bias, model explainability, or data provenance.
3. Integrate AI-Specific Risk Controls
- AI Risk Identification: Add controls for data quality, model performance, and potential bias.
- Risk Assessment: Include likelihood, impact, and regulatory consequences of AI failures.
- Mitigation Strategies: Document methods like model testing, monitoring, human-in-the-loop review, or bias audits.
- Governance & Accountability: Assign clear ownership for AI system oversight and compliance reporting.
4. Ensure Regulatory and Ethical Alignment
- Map your AI systems against applicable standards:
- EU AI Act (high-risk AI systems)
- GDPR or HIPAA for data privacy
- ISO 31000 for general risk management principles
- Document how your policy addresses ethical AI principles, including fairness, transparency, and accountability.
5. Update Policy Language and Procedures
- Add a dedicated “AI Risk Management” section to your policy.
- Include:
- Scope of AI systems covered
- Risk assessment processes
- Monitoring and reporting requirements
- Training and awareness for stakeholders
- Ensure alignment with ISO 42001 clauses (risk identification, evaluation, mitigation, monitoring).
6. Implement Monitoring and Continuous Improvement
- Establish KPIs and metrics for AI risk monitoring.
- Include regular audits and reviews to ensure AI systems remain compliant.
- Integrate lessons learned into updates of the policy and risk register.
7. Documentation and Evidence
- Keep records of:
- AI risk assessments
- Mitigation plans
- Compliance checks
- Incident responses
- This will support ISO 42001 certification or internal audits.
AI Compliance in M&A: Essential Due Diligence Checklist
DISC InfoSec’s earlier posts on the AI topic
AI is Powerful—But Risky. ISO/IEC 42001 Can Help You Govern It
Secure Your Business. Simplify Compliance. Gain Peace of Mind
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