Description
Many organizations already have AI inside live workflows, but very few can explain how those workflows are governed under ordinary use and under pressure. Controls are partial, decision rights are muddy, evidence is scattered, and human oversight often exists more as a slogan than a working system. Operational AI Readiness is written to close that gap.
This book is for teams that need to make live AI workflows legible, reviewable, and defensible. It shows how to classify real decision influence, build approval gates, create an evidence spine, design human oversight that survives contact with operations, and run a readiness sprint that produces artifacts instead of aspiration.
Inside the book:
- A practical framework for inventorying consequential workflows and classifying where AI actually affects decisions
- Guidance for approval gates, evidence logging, human review design, and vendor due diligence
- A 30-day readiness sprint built around operational outputs teams can actually produce
If your organization is already running AI and needs governance that works in practice, this book is built for that stage.


