Executive summary

A diagnostic that tells finance and transformation leads whether an AI proposal has a measured baseline and credible evidence before it becomes a business case. Its outcome is one of three: proceed, close specific evidence gaps first, or stop and reframe.

What is inside

What this asset covers

The asset includes a structured questionnaire, a graded evidence hierarchy and inventory, and a weighted scoring model with anchored levels and an explicit decision rule. It writes out the formulas for current and future unit cost, NPV and payback, and keeps released capacity separate from cash. It also contains a fully worked synthetic case, a failure case, an alternate scenario and a practice exercise, along with role-based execution, governance and measurement tables and copyable working templates.

  • 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