A maturity diagnostic that answers who is accountable for each AI system and its outcomes, and whether that accountability holds up in practice. It turns the answer into scored capability dimensions and a sequenced list of gaps to close.
What this asset covers
The asset sets out a repeatable assessment method with written formulas, an anchored scoring rubric with evidence caps, and outcome measures for ownership coverage, exception backlog and review discipline. It compares accountability operating models and keeps cash cost separate from staff capacity. It also provides role-based execution, governance and measurement tables, a dated summary of the EU AI Act timeline changes, a synthetic worked case with a failure case, a calibration exercise, and editable registers and logs.
- Purpose and decision
- Context and applicability
- Inputs and evidence
- Definitions and assumptions
- Method and analytical logic
- Current-state assessment
- Options and business case
- Recommended design
- Execution and activation
- Governance and risk
- Measurement and benefits
- Worked example and practice
- Working tools and references