AI-Native Maturity Model™
A seven-level model for classifying how an organization evolves from manual operations and isolated AI usage toward governed autonomy and recursive intelligence.
Measure ReadinessAnalog Organization™
Work and coordination are predominantly manual. AI has no meaningful place in the operating architecture.
AI-Assisted Organization™
Individuals use AI tools to improve tasks, but capability remains personal, isolated, and dependent on manual coordination.
AI-Enabled Organization™
AI is integrated into selected workflows and business functions, with emerging standards and shared capability.
AI-Operationalized Organization™
AI-supported workflows are standardized, measured, governed, and increasingly embedded in repeatable operations.
AI-Native Organization™
Intelligence is designed as organizational infrastructure across governance, decisions, execution, learning, and architecture.
Autonomous Enterprise™
Governed autonomous systems execute substantial operational work with intentional human intervention boundaries.
Recursive Intelligence Organization™
Intelligent systems coordinate, improve, govern, and create work for other intelligent systems through managed recursive loops.
Maturity tells you what state the organization resembles. Readiness tells you what evidence supports that state.
ANMM™ is the classification model. ANRA™ is the diagnostic methodology. ANRS™ is the normalized readiness score. Keeping these concepts separate prevents a strong score in one area from being mistaken for whole-organization architectural maturity.
The objective is not to race toward maximum autonomy.
Organizations should advance only when governance, architecture, identity, knowledge, interoperability, observability, and human intervention controls are capable of supporting the next operating state. Higher autonomy without stronger architecture increases fragility rather than maturity.