Insight
How can organizations implement AI governance?
Organizations can implement AI governance by inventorying AI use cases, defining risk ownership, aligning policies to a framework such as NIST AI RMF, setting approval and monitoring processes, securing AI systems, and documenting how AI risks are measured and managed.
Implementation steps
- Create an AI system inventory
- Classify AI use cases by risk and data sensitivity
- Define roles for business, legal, security, privacy, and technology owners
- Adopt control requirements for high-risk use cases
- Monitor model, data, security, and operational risks
Evidence to maintain
- Use case approvals
- Risk assessments
- Data handling decisions
- Security reviews
- Human oversight procedures
- Incident and change records
Frequently asked questions
- Who owns AI governance?
- AI governance is shared across leadership, legal, privacy, security, data, technology, and business owners.
- Where should a company start?
- Start with an AI inventory and risk tiering process before buying additional tools.