Somewhere ahead of you, someone with authority will ask you to prove your AI is governed.
It could be an acquirer in diligence, a regulator opening an inquiry, an auditor in fieldwork, or your own board in a moment that does not feel quiet. The question is the same in every version. The companies that can answer it produce a signed document. The companies that cannot improvise a narrative.
The AI Risk & Governance Review™ closes that gap. It is the structured, evidence-based operating discipline that produces governance you can hand across the table, sized for the business you actually run, before someone asks for what you don't have.
Volume III of The Operating Discipline for AI Library™ is written for owners, presidents, CFOs, COOs, general counsels, and boards running organizations between 20 and 1,000 employees. It is written for executives who would rather defend their AI before someone challenges it.
Inside, Stephen R. Jordan walks leaders through:
- The four AI risk categories every framework maps to: data, decisions, vendors, and compliance
- A five-level AI Data Exposure Model™ and a four-tier Decision Influence Matrix™ sized to act in weeks, not quarters
- The 6-Step Review Process™ that produces a signed governance dossier for every material AI use case
- The AI Governance Framework Crosswalk™: the line-by-line mapping between the operating artifacts and ISO/IEC 42001, the NIST AI Risk Management Framework, the EU AI Act, SR 11-7, NYC Local Law 144, the newer EU and international instruments (DORA, NIS2, the Revised Product Liability Directive, the Council of Europe Framework Convention on AI), and the sector rules in healthcare, financial services, insurance, and education
- Three new operating logs that satisfy ISO 42001 Clauses 9 and 10: the AI Internal Audit Workpaper Log™, the AI Management Review Minutes Log™, and the AI Corrective Action Register™
- The AI Board Reporting Package™ that turns quarterly minutes into defensible director oversight
- The AI Incident Response Framework™ for when an AI use case produces an outcome that is wrong, harmful, or under inquiry
- A 90-Day Governance Launch Plan™ that runs on named owners and existing meetings
About the author
Stephen R. Jordan is the founder of SRJ Consulting & Services LLC, an operator-led AI advisory practice based in Frisco, Texas. He is the author of The Operating Discipline for AI Library™, a nine-volume canon on running AI as a permanent business function. His career spans senior consulting, operational, and security roles at organizations including Citi, Optiv, Intel, and McAfee.
Volume III sits inside Pillar I: AI Business Services™, alongside Volume I (The AI Business Enablement Audit™) and Volume II (The AI Readiness & Performance Assessment™). Each volume stands on its own. Read together, they form an installed operating discipline for AI as a permanent business function.
Companion materials, including editable versions of every governance instrument in the book, are available at srjconsultingservices.com/books.
