AI Readiness Assessment
An AI readiness assessment rates six dimensions as red, amber, or green with evidence attached, and is applied to a specific use case rather than to the organisation in general. Green on data requires that a sample has been inspected, quality verified, access granted, and lawful basis confirmed.
Readiness is a property of a use case in an organisation, not of the organisation alone. An institution can be ready for one system and entirely unready for another running on different data.
The template
Six dimensions, assessed as red, amber, or green with evidence. Assess the specific use case, not the organisation in general.
| Dimension | Green requires |
|---|---|
| Data | Sample inspected, quality verified, access granted, lawful basis confirmed |
| Process | Current process documented as performed, baseline measured |
| People | Business owner committed, reviewers identified and available |
| Platform | Deployment path exists, monitoring available, rollback tested |
| Governance | Consequence tier assigned, gate requirements known, stopping condition drafted |
| Funding | Implementation and first operating year funded, not only the pilot |
Any red on Data or People means the use case is not ready to start. Red on Platform or Governance means it can start with a defined remediation plan and a hold at the go live gate.
How to use it
- Assess the specific use case. An organisation-level readiness score cannot tell you whether this system can be built.
- Require evidence for every green. A green without an inspected data sample is an opinion.
- Treat amber as work to be scheduled rather than a soft pass, and red as a precondition that has to be met before delivery starts.
- Re-run the assessment when the use case changes scope, because readiness does not transfer between problems.
Common questions
What is an AI readiness assessment?
An assessment of whether a specific AI use case can actually be delivered in a given organisation, rated across six dimensions as red, amber, or green with evidence attached. Green on data requires that a sample has been inspected, quality verified, access granted, and lawful basis confirmed. It assesses the use case rather than the organisation, because readiness does not transfer between problems.
What is the difference between AI readiness and AI maturity?
Readiness asks whether a specific use case can be delivered now, assessed against that case with evidence. Maturity describes the organisation’s general capability across data, delivery, governance, operations, and people. An organisation can be mature overall and unready for a particular system whose data is unusable.