A scoring diagnostic for deciding which AI use cases are ready to fund. It uses evidence-based readiness anchors and value modelling that separates freed-up capacity from real cash, and sends every unready case to a named gap with an owner.
What this diagnostic covers
It contains:<ul><li>a seven-dimension readiness rubric with anchored levels and rules that limit scores based on how strong the evidence is</li><li>written formulas for value and cost per task</li><li>gate rules and a prioritization quadrant</li><li>a regulatory exposure check that routes flagged cases to legal review, with reference to EU AI Act timelines and NIST and ISO/IEC guidance</li><li>a calibration routine built around a shared case</li><li>execution, governance and KPI tables</li><li>a synthetic multi-case example with a failure case, an alternate scenario and an exercise</li><li>editable intake, scoring, value, gap register and calibration templates</li></ul>
- 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