AI adoption checklist for leadership teams

A practical checklist to align governance, data readiness, and measurable outcomes before scaling AI.

Scaling AI is not primarily a tooling problem—it’s an operating model problem.

Checklist:

1) Define measurable outcomes (KPIs) before model selection.

2) Validate data readiness: quality, access, lineage, and privacy constraints.

3) Set governance: ownership, approval flow, and monitoring expectations.

4) Start with a pilot that has a clear production path.

5) Create enablement: training, playbooks, and adoption support.

If you want, we can map your first AI pilot and scaling plan in a single consultation.