Enterprise AI Maturity Model

The weakest domain in a consequential path is the maturity that counts.

Assess maturity per application by the responsibilities it can govern across identity, context, policy, state, human judgment, external effects, evidence, and operations.

Application ResponsibilityWeakest DomainStage GatesEvidence
Application Responsibility

Start with the application responsibility this page owns.

Evidence

Connect the concept to evidence and implementation.

Assessment model

Two rules decide whether this model is useful

The model keeps maturity grounded in what an application can actually govern when the outcome matters.

Weakest domain

The weakest consequential responsibility sets the practical maturity of the application path.

Platform purchase is not maturity

Buying infrastructure does not prove that a specific application path governs identity, context, policy, state, and evidence.

Per application

Assess maturity on each consequential application, not at the enterprise-logo level.

Evidence required

A maturity claim should be backed by observable artifacts, tests, and operating proof.

Six levels

Measure maturity by application responsibility

The levels move from experiments to governed, explainable, scalable application operation.

Level 1 - Prompt Experiments

Individual use cases rely on ad hoc prompts or assistants.

Level 2 - Assisted Workflows

AI supports work, but application responsibilities remain fragmented.

Level 3 - Governed Application Path

Identity, context, policy, state, and review begin to stay connected.

Level 4 - Explainable Operation

Evidence, lineage, replay, and controlled actions support operational accountability.

Level 5 - Scaled Application Factory

Teams can build repeated governed applications without rebuilding core responsibilities.

Level 6 - Adaptive Operating Model

Maturity evidence, economics, quality, and governance guide continual expansion.

Assess the application, not the enterprise logo.

Use the maturity model to identify which responsibility limits a real AI application path and what evidence would move it forward.