Most AI programs still celebrate the wrong milestone. Seats activated. Logins counted. A dashboard that flips green the week everyone gets access.
That number is easy to report. It is also the wrong one.
Capability is not readiness. You can hand someone a model and watch them use it worse than the workflow it replaced, and the dashboard will still call it success. The gap is not technical. It is human: judgment, practice, and the muscle memory that makes a tool change how work actually gets done.
I build the layer underneath the license. Curriculum that teaches discernment, not just clicks. Measurement that tracks behavior change, not activation. Support structures that let skeptics and early adopters learn in the same room without pretending everyone starts in the same place.
Technical AI capability times human readiness. Multiplicative, not additive. Zero on either side and the whole program collapses, no matter how good the model is.
What would it take for your organization to measure readiness, not just access?