Datasets / AI Agent Governance Maturity Model

AI Agent Governance Maturity Model

Five levels to assess and advance how an organization governs autonomous AI agents.

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Level	Stage	Characteristics
1	Ad hoc	Agents deployed without identity, policy or audit; behavior is opaque.
2	Logged	Actions are recorded after the fact, but not constrained in real time.
3	Controlled	Scoped permissions and basic policy enforcement; human approval for high-impact actions.
4	Governed	Multi-layer governance: verifiable identity, deterministic policy, mediated execution, immutable audit.
5	Autonomous & accountable	Fleets of orchestrated agents operate autonomously within deterministic guardrails, fully transparent and reversible.

Target state. Level 4–5 is where autonomous AI becomes safely deployable at enterprise scale — the design goal of AINOVA's Multi-Layer Governance Architecture.

Model by Gianluca Busato, Enkronos ecosystem.