Leadership and Purpose
Treat AI as strategic business redesign, define ownership, and preserve long-term agency as dependency grows.
Board-Level AI Stewardship
The Board's Guide to Corporate AI Governance
Stewardship, Strategy, and Accountability in the Age of AI
A practical handbook for chairs, non-executives, audit and remuneration committees, general counsel, company secretaries, chief risk officers, and advisers who need to govern AI as a material feature of strategy, control, people, and trust.
Why This Book
AI has moved into decisions, controls, workforce change, and stakeholder trust
Artificial intelligence is no longer sitting at the edge of the enterprise as a specialist experiment. It is shaping prices, approvals, hiring, customer interactions, surveillance, escalation, and reporting. Once AI starts influencing consequential outcomes, it stops being only a technology matter and becomes a board matter.
This book argues that boards do not need to become technical committees, but they do need a governance discipline that is specific enough to handle decision rights, override, explainability, dependency, assurance, workforce transition, and disclosure.
The Corporate AI Governance Code
A board-ready framework organised around six governance domains
Division of Responsibilities
Clarify board, committee, and executive accountability so AI governance is coherent across the organisation.
Decision-Making and Control
Document how AI advises, automates, and acts, with named human accountability for material outcomes.
Risk, Assurance and Internal Control
Integrate AI into enterprise risk, lifecycle control, intervention capability, assurance, security, and data governance.
People, Culture and Remuneration
Govern workforce transition, incentives, trust, and the changing contract between employer and employee.
Transparency and Accountability
Ensure disclosure, recordkeeping, challenge, and evidence are strong enough to support real accountability.
Inside the Book
From the case for governance to a practical maturity model and annual operating rhythm
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01
Why Corporate AI Governance Is Needed
Why AI is now a board matter, why existing governance is necessary but insufficient, and why boards must integrate the full picture.
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02
The Corporate AI Governance Code
A proposed comply-or-explain code for boards covering scope, definitions, principles, and detailed provisions.
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03
Section A: Leadership and Purpose
Board ownership of AI strategy, technological dependency, resilience, and strategic optionality.
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04
Section B: Division of Responsibilities
Governance structure, executive accountability, board competence, and independent scrutiny.
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05
Section C: Decision-Making and Control
Decision classification, override, escalation, high-stakes review, and agentic operations.
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06
Section D: Risk, Assurance and Internal Control
AI risk taxonomy, lifecycle controls, third-party due diligence, security, data governance, and transaction oversight.
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07
Section E: People, Culture and Remuneration
Workforce impact, reskilling, transition, culture, trust, and incentives for responsible AI adoption.
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08
Section F: Transparency and Accountability
Disclosure, stakeholder communication, evidence, challenge, and the conditions for credible accountability.
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09
AI Governance Maturity Assessment
A structured maturity model that helps boards distinguish between credible progress and performative oversight.
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10
Implementation Roadmap and Annual Governance Cycle
A practical operating rhythm for committees, management reporting, evidence gathering, and annual review.
Who It Is For
Written for people carrying real stewardship responsibility
Board chairs and non-executive directors
Audit, risk, and remuneration committee chairs
General counsel and company secretaries
Chief risk officers and internal audit leaders
Institutional advisers and governance specialists
Senior executives shaping AI operating models
Built for Use
Designed as a working handbook, not just a commentary
Board and Committee Reviews
Use the code provisions, maturity questions, and governance expectations to structure agendas and challenge management reporting.
Documentation and Evidence
Translate governance intent into tangible artefacts, evidence trails, and records that show AI oversight is operating.
Maturity Assessment
Pressure-test whether AI governance is emerging, disciplined, and resilient rather than ceremonial or fragmented.
Implementation Planning
Move from principles to operating rhythm with a roadmap that boards and executives can actually run through the year.
Availability
Amazon release details will be added here once the listing is live
The book is being prepared for Amazon. As soon as the listing is available, this section and the main call-to-action buttons will be updated with the direct purchase link.
Amazon Listing Coming Soon
Bring It Into the Boardroom
Use this book to sharpen AI oversight before governance gaps become visible through failure
Contact Vincent A. Powell for book enquiries, speaking, governance workshops, advisory support, or board and committee sessions focused on AI accountability.