ACCOUNTABLE : A CFO's Framework for Governing AI Before You're Asked to Defend It
Language: English
Published by Independently Published Jun 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 35.95
Quantity: 2 available
Add to basketItem description from seller
Neuware - Your organization is using AI. The question is whether anyone has built the system to govern it. Not a policy document. Not an ethics statement. A working governance system with ownership at every level, cost visibility your board can act on, and an accountability chain that does not end at 'the vendor handles that.' Most AI governance books are written by consultants observing from the outside or academics studying the problem in theory. This one was written by a sitting CFO who manages a billion-dollar capital improvement program, oversees a $65M operating budget, and answers to a governing board. The frameworks in this book were built because they had to work under real institutional scrutiny, not because they tested well in a workshop. Accountable is built around the FACT Framework: Fairness, Accountability, Compliance, and Transparency. It gives senior leaders a structured, repeatable system for governing AI with the same rigor they already apply to financial controls and regulatory compliance. What this book delivers that others do not: A maturity scoring system (the FACT AI Governance Score) that gives your organization a baseline today and a measurable target for next quarter. Not a philosophical model. A numeric assessment you can present to your board. A 90-day governance sprint plan that moves from assessment through implementation. Not a multi-year roadmap. A deployment timeline that fits inside one budget cycle. Board-ready reporting templates built by someone who writes board reports for a living. Not slide deck concepts. Actual templates you can adapt to your governance structure. A cost framework (Total Cost of AI Ownership) that quantifies what AI governance actually costs, so you can budget for it instead of discovering it after the audit findings. An accountability chain model that assigns ownership at every level, from the board resolution to the frontline user, so governance does not stall at 'someone should look into that.' This book was not written for AI engineers, data scientists, or technology teams. It was written for the people who will be asked to explain, defend, and account for how their organization governs AI: CFOs, board members, general managers, compliance officers, internal auditors, and the senior leaders who sign off on what the organization builds, buys, and deploys. The companion Accountable Governance Toolkit (available separately) provides the Excel-based implementation tools: FACT score sheets, board templates, cost models, and the full 90-day sprint plan.…
Seller Inventory # 9798995520818
- Title
- ACCOUNTABLE : A CFO's Framework for Governing AI Before You're Asked to Defend It
- Author
- Brian H Zahn
- Publisher
- Independently Published Jun 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798995520818
- Item weight
- 276 grams
- Dimensions
- 229x152x11 mm
Your organization is using AI. The question is whether anyone has built the system to govern it.
Not a policy document. Not an ethics statement. A working governance system with ownership at every level, cost visibility your board can act on, and an accountability chain that does not end at 'the vendor handles that.'
Most AI governance books are written by consultants observing from the outside or academics studying the problem in theory. This one was written by a sitting CFO who manages a billion-dollar capital improvement program, oversees a $65M operating budget, and answers to a governing board. The frameworks in this book were built because they had to work under real institutional scrutiny, not because they tested well in a workshop.
Accountable is built around the FACT Framework: Fairness, Accountability, Compliance, and Transparency. It gives senior leaders a structured, repeatable system for governing AI with the same rigor they already apply to financial controls and regulatory compliance.
What this book delivers that others do not:
A maturity scoring system (the FACT AI Governance Score) that gives your organization a baseline today and a measurable target for next quarter. Not a philosophical model. A numeric assessment you can present to your board.
A 90-day governance sprint plan that moves from assessment through implementation. Not a multi-year roadmap. A deployment timeline that fits inside one budget cycle.
Board-ready reporting templates built by someone who writes board reports for a living. Not slide deck concepts. Actual templates you can adapt to your governance structure.
A cost framework (Total Cost of AI Ownership) that quantifies what AI governance actually costs, so you can budget for it instead of discovering it after the audit findings.
An accountability chain model that assigns ownership at every level, from the board resolution to the frontline user, so governance does not stall at 'someone should look into that.'
This book was not written for AI engineers, data scientists, or technology teams. It was written for the people who will be asked to explain, defend, and account for how their organization governs AI: CFOs, board members, general managers, compliance officers, internal auditors, and the senior leaders who sign off on what the organization builds, buys, and deploys.
The companion Accountable Governance Toolkit (available separately) provides the Excel-based implementation tools: FACT score sheets, board templates, cost models, and the full 90-day sprint plan.
"Synopsis" may belong to another edition of this title.
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