Most AI maturity models grade the tooling: model selection, MLOps, data infrastructure, governance frameworks. That's necessary work. It isn't sufficient work.
The real readiness question is operational. Are ownership lines clear in the workflows AI will touch? Do KPIs align across the teams that will use the model? Is workflow continuity stable enough that automation has something to automate? Is workforce strategy positioned to absorb the change?
Until those answers are yes, AI is being deployed onto fragmented operations — and the model will scale the fragmentation. Operational maturity is the prerequisite to AI maturity. Always.