AI Governance Maturity Model
What This Requires
Adopt or develop AI governance maturity model with levels (Initial, Developing, Defined, Managed, Optimizing). Assess current maturity annually, identify gaps, and prioritize improvements to advance maturity level.
Why It Matters
Maturity models provide roadmap for continuous improvement. They enable benchmarking against peers and justify investment to leadership.
How To Implement
Choose/Develop Model
Use existing model (NIST AI RMF Maturity, ISO 42001 Levels) or create custom. Define 3-5 levels with criteria per domain (Govern, Build, Secure, Deploy, Monitor, Improve).
Conduct Assessment
Annually, evaluate current state per domain. Document evidence supporting maturity level. Identify gaps (e.g., "Monitor: Level 2, need automated drift detection for Level 3").
Prioritize Roadmap
Rank gaps by impact and effort. Build 12-month roadmap targeting next maturity level. Assign owners and deadlines.
Track Progress
Quarterly check-ins on roadmap progress. Update maturity assessment when improvements completed. Report progress to leadership.
Evidence & Audit
- Maturity model document with level definitions
- Annual assessment results with evidence
- Gap analysis and prioritization
- Improvement roadmap with owners and deadlines
- Quarterly progress reports