DECISION-SPECIFIC SCOPE
AI Readiness Assessment: scope, evidence and acceptance
An AI readiness assessment examines business goals, workflows, data access, skills, governance and change capacity together. The outcome is not a vanity score The page is intentionally bounded around the decisions below so it does not compete with adjacent services through generic, repeated claims.
01Operating audience and ownership
The engagement begins by identifying which of these roles owns the decision, supplies evidence and will operate the resulting change.
- Boards and executive teams
- Transformation and innovation leaders
- Business functions adopting generative AI
02Constraints that must be evidenced
The problem statements are tested against real examples, existing systems and failure consequences rather than accepted as tool requirements.
- Disconnected tool experiments without investment priorities
- No shared view of value, data, risk and ownership
- Technology plans that ignore workforce adoption
03Controlled starting points
The first pilot is deliberately narrow: one workflow, representative cases, visible human control and evidence that supports a scale decision.
- Executive and team interviews
- Workflow, data and tool inventory
- Skills and governance review
- Ready-prepare-wait opportunity matrix
Defined handoverThe expected handover is organised around Current-state and opportunity summary; Prioritised use-case portfolio; Pilot cards and success criteria; Roadmap, ownership and adoption plan. Each item must identify its source evidence, owner, review point and the next decision it supports.
What makes this page distinct
A readiness assessment is diagnostic. It identifies what is ready, what requires data or governance preparation and what should wait; it does not disguise an implementation sale as a maturity score.