AI Capability Evidence Framework
Last updated: 2026-08-14
The capability evidence framework records one row per affected role: the capability required, what counts as evidence of it, where that evidence is recorded, and when it is reassessed. This is what turns a training programme into a durable organisational expectation rather than an event.
Training that is not recorded as an expectation decays within a year and has to be repurchased. Evidence attached to roles survives staff turnover in a way that attendance records do not.
The template
For each affected role, complete this row. This is the document that turns a programme into a durable expectation.
| Role | Capability required | Evidence of capability | Where it is recorded | Reassessed |
|---|---|---|---|---|
| Example: service manager | Can assess whether a proposed system should be adopted in their service | Completed use case assessment reviewed by the CoE | Annual objectives | Yearly |
| Example: data engineer | Can design and run an evaluation against live-like data | System passing internal gate | Role profile and objectives | Yearly |
How to use it
- Complete one row per affected role rather than per course.
- Define evidence as something observable, not attendance.
- Record it in the system that already governs the role, so it survives the programme that created it.
- Set a reassessment interval, because capability claims age as tools change.
This template comes from the AI Leadership and Workforce Capability: A Practical Playbook, which sets out the reasoning behind it, the rules of thumb that govern its use, and the signals that tell you the approach is failing. The full playbook is also available as Markdown. See all AI governance templates.