Who it is for
For leaders who need to know where their organization's AI maturity stands on the governance, lineage, and audit-trail gaps regulators will scrutinize next.
Benchmark your organization's AI maturity against the governance, lineage, and audit-trail gaps regulators will scrutinize next.

This is a workbook, not a survey of the field. Every exercise ends with something you build: a register, a diagram, a score, a roadmap. Two things about your organization are probably both true right now—and they don't fit together.
Eleven months after a consumer lender finished its first AI governance assessment, the regulator behind that inquiry scheduled a routine follow-up on the credit-decisioning model that approves and prices its personal loans. The first review had gone cleanly. The model had not failed.
For leaders who need to know where their organization's AI maturity stands on the governance, lineage, and audit-trail gaps regulators will scrutinize next.
You can pick the highest-impact AI system on your inventory—a benefits-eligibility model, a resume screener, a clinical-triage score, a pricing engine—and answer the plain question a regulator will point at one specific output and ask: Why did this person get this result?
You'll see why you can pass every single-system test in this workbook and still fail an audit—just as a regional hospital network claimed "strong AI governance" because its flagship sepsis-alert model had a clean lineage diagram and an immutable decision log.
You'll be ready for what a real regulator actually does: not ask whether you have an AI policy, but ask you to produce the approval record for a specific model on a specific date—and explain who signed off on the data it was trained on.
You'll turn a pile of findings into a sequence your engineering and compliance teams can execute, instead of the result paper policies get—everything looks important, so nothing moves. A roadmap is what makes the difference.
The gap is rarely a dramatic failure. It shows up as small, specific inabilities, and you recognize your own readiness by which you can answer without a meeting—starting with the inventory question: how many AI or automated decision systems are in production right now, including models embedded in software you bought rather than built?
Set aside thirty minutes. For the organization you chose, work through the diagnostic and record a score for each item. It's a self-assessment, so the value is in candor, not in a high number.
You're a VP of operations whose team adopted a vendor's AI-driven scheduling tool that decides which staff work which shifts. Everyone understands it, usage is high, and the board has heard a confident update on its efficiency gains. By the fluency measure, you look ready—until you apply the four probe questions.

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