Two years into mainstream GenAI, the differentiator is no longer curiosity. It is capability. Five skills consistently show up in leaders whose teams actually ship value.
1. Task decomposition
Breaking a deliverable into inputs, steps and checks — the single highest-leverage skill, because it makes work legible to both people and models.
2. Context engineering
Knowing what to feed a model: house style, prior examples, constraints, and the audience. Better context beats clever wording every time.
3. Verification discipline
Building a habit of checking claims, numbers and citations before anything leaves the team. Speed without verification is simply faster risk.
4. Data and confidentiality judgement
Understanding what may be shared, what must be anonymised and where approved tooling ends. This is now a basic duty of care, not an IT concern.
5. Coaching the team
Leaders who demonstrate their own workflows in the open create adoption. Leaders who delegate GenAI to a pilot group create shelfware.
None of these are technical. All of them are learnable in weeks — with real work, real feedback and a little structured practice.