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This document defines how organizational AI transformation maturity is determined using three interrelated components:
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AI transformation maturity cannot be represented by a single metric.
Instead, maturity reflects the interaction of:
These correspond to:
Each pillar is scored on a five-point scale:
| Score | Meaning |
|---|---|
| 0 | Not present / no evidence |
| 1 | Ad hoc / experimental |
| 2 | Repeatable but inconsistent |
| 3 | Defined and institutionalized |
| 4 | Optimized / continuously improving |
Scores should reflect observable practices and artifacts, not intentions.
Pillar scores indicate how prepared the organization is to support higher autonomy.
Levels describe the dominant mode of software development:
Levels are determined by how work actually flows from intent to deployed outcomes.
Organizations often operate across multiple levels simultaneously.
Stage gates represent hard constraints that must be satisfied before safely operating at higher levels.
Typical gate conditions include:
Gates prevent unsafe progression driven by enthusiasm rather than readiness.
Overall maturity is determined by the minimum of three factors:
The level that best describes how most new work is delivered.
Whether pillar scores indicate sufficient capability to sustain that level.
Severe weaknesses in critical pillars may downgrade effective maturity.
Failure to meet required gates blocks advancement regardless of other factors.
Most organizations exhibit mixed maturity:
Assessments should identify both the dominant level and high-risk mismatches.
High scores in isolated pillars do not imply readiness for higher autonomy.
Common imbalance patterns include:
Balanced capability development is required for sustainable transformation.
This system is designed for facilitated organizational evaluation involving:
Structured discussion is essential for interpreting results correctly.
This framework:
It is intended as a decision-support tool for transformation planning.