Practical Guide to Implementing AI Risk Management in Compliance with NIST AI RMF and ISO Standards

As a technical compliance executive looking for practical guidance on setting up an AI risk management program efficiently to align with the AI Management System (AIMS), I felt like it was important to revise the original guide "The Business of Compliance - Integrating NIST AI RMF and ISO Standards for AI Governance and Cybersecurity" to include a more action-oriented approach.  

This updated article is designed to provide you with a clear, actionable approach to setting up an AI risk management program aligned with the NIST AI Risk Management Framework (AI RMF) and the ISO/IEC 42001 AI Management System standards. A link to the NIST-supplied RMF-AIMS mapping is provided below. 

Step-by-Step Implementation:

1. Policy Alignment and Objective Setting: Begin by aligning your AI policies with your business objectives. Establish clear, measurable goals for your AI systems, ensuring they comply with legal and regulatory requirements.
2. Risk Assessment Process: Implement a comprehensive risk assessment process. Identify potential risks, categorize them based on impact, and develop mitigation strategies. Regularly review and update your risk assessments to address new challenges.
3. Engaging Suppliers: Develop criteria for selecting AI technology suppliers. Ensure they adhere to your risk management standards and conduct regular compliance checks.

Continuous Monitoring and Improvement: Set up systems for continuous monitoring of your AI risk management program. Regularly review and adjust your strategies based on performance data and emerging risks. 

Legal and Regulatory Compliance: Stay informed about relevant legal and regulatory changes. Integrate these into your risk management framework and ensure your AI systems remain compliant. 

References

• NIST AI RMF to ISO/IEC 42001 Crosswalk: A vital resource for understanding the integration of NIST AI RMF and ISO standards, offering insights into legal and regulatory requirements, policy development, and risk management processes for AI systems.

Call to Action

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