Five Levels of AI Governance Maturity
The Clariantix maturity model classifies AI governance into five levels: ad-hoc, defined, managed, measured, and optimizing. Knowing the current level — and the next one — is the first step in any improvement program.
Level 1 — Ad-Hoc
AI use is happening; governance is informal. There is no inventory, no classification, and no single accountable executive. Risk is unknown, not necessarily high — but unknown.
Level 2 — Defined
Policies exist. Inventory has been started. An executive is named. Governance is documented but not consistently operated. The risk of drift is high.
Level 3 — Managed
Governance is operated to a cadence. Inventory and classification are kept current. Vendor AI is brought inside the perimeter. Reporting reaches the executive committee on a defined schedule.
Level 4 — Measured
Maturity is baselined and re-measured on a recurring cadence. Improvement targets are published. Boards receive quarterly reporting with trend data. Evidence is produced on request.
Level 5 — Optimizing
Governance is integrated into product, procurement, and operating cadences by default. External validation is sought and earned. The organization is recognized as a trusted operator of AI in its markets.
"Most organizations are between levels two and three. The work to reach level four is what unlocks board confidence."
- Five levels: ad-hoc, defined, managed, measured, optimizing.
- Most organizations sit between levels two and three.
- Reaching level four is what unlocks board confidence.
- Each level has a defined set of capabilities — improvement is sequenced, not heroic.