Why Tooling Isn't the Bottleneck
Most organisations don't fail at AI adoption because they lack access to models or tools — those are now widely available. They fail because they don't have a clear, sequenced plan for which teams build which capability first, and in what order.
The Sequencing Problem
Rolling out AI capability to every team simultaneously tends to produce shallow adoption everywhere rather than real capability anywhere. A small number of teams building deep, evidenced capability first creates internal reference points the rest of the organisation can learn from.
A Practical Framework for Rollout
Start with role-specific skill assessment to understand where the real gaps are, not assumptions about them. Follow with structured, practical skill-building tied to real work, then verification through completed projects — not just training completion.
Measuring Progress Honestly
Course completion rates and training hours are weak signals of actual capability. Stronger signals include completed projects, assessed skill scores, and — over time — a measurable shift in what kinds of work a team can take on.