The AI Governance Flywheel is a practical framework your organization can adopt to align standards, regulations, and governance processes in a dynamic cycle of continuous improvement.
It shows how standards, regulations, and governance practices reinforce each other in a cycle of continuous improvement.
AI Governance Flywheel
1. Standards & Frameworks
- ISO/IEC 42001 (AI Management System)
- ISO/IEC 23894 (AI Risk Management)
- EU AI Act
- NIST AI RMF
- OECD AI Principles
➡️ Provide structure, terminology, and baseline practices.
2. Regulations & Policies
- EU AI Act
- U.S. Executive Order on AI (2023)
- China AI Regulations
- National/sectoral guidelines (healthcare, finance, defense)
➡️ Drive compliance requirements and enforce responsible AI.
3. Governance & Controls
- AI Ethics Boards
- Risk Assessment & Mitigation
- AI Transparency & Explainability
- Data Governance & Privacy (GDPR, CCPA)
➡️ Ensure AI use is aligned with business values, laws, and trust.
4. Implementation & Operations
- AI System Lifecycle Management
- Model Monitoring & Auditing
- Bias/Fairness Testing
- Incident Response for AI Risks
➡️ Embed governance in day-to-day AI operations.
5. Continuous Improvement
- Internal & external audits
- Feedback loops from incidents/regulators
- Updating models, policies, and controls
- Staff training and culture building
➡️ Enhances trust, reduces risks, and prepares for evolving standards/regulations.
📌 The flywheel keeps spinning:
Standards → Regulations → Governance → Operations → Improvement → back to Standards.
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