Leading AI: Direction Before Destination
What Boards and Executives Need to Decide
What This Book Covers
Every large organization is now under pressure to set an AI direction. The board is asking. Competitors are moving. Regulators are watching. Few leaders have a decision framework that holds up when the technology keeps shifting underneath them.
This book is for the people who have to decide: boards, C-suite executives, and general counsel. It lays out the AI Readiness Framework, six dimensions across five maturity levels, and the questions you need to answer before you commit to anything. Strategy. Implementation. Data. People. Governance. Scale.
The argument is straightforward: in fast-moving environments, fixed destinations become liabilities. You set direction first, and the destination clarifies as you move. The book draws on two decades of consulting in technology transformation, combined with hands-on AI implementation work. It's the framework the author wished existed when clients started asking "what should we actually do about AI?"
Who this book is for
- ✓ Board members navigating AI exposure, oversight, and governance
- ✓ C-suite executives setting AI direction across the organization
- ✓ General counsel and chief compliance officers managing AI risk
- ✓ Senior advisors and consultants supporting AI adoption at scale
What's Inside
10 chapters across three sections
Introduction & Context
Introduction
How this book came about and why it takes a different approach. Written in collaboration with AI, it practices what it preaches — using AI as a thought partner throughout the writing process.
Chapter 1: Beginning with AI
The state of AI in 2026 — what it is, what it can do, and how we got here. Cuts through the noise to give decision makers a clear picture of AI capabilities, limitations, and the landscape they're navigating.
The AI Readiness Framework
Chapter 2: Understanding AI & Technology
You can't lead what you don't understand. Covers core AI concepts, integration patterns like MCP, and strategies for building the right level of technical literacy across your organization.
Chapter 3: Strategy & Vision
Stop chasing shiny AI toys. Start by asking what business problem you're solving. Covers build vs buy vs partner decisions, measurement frameworks, and how to create an AI strategy that connects to business outcomes.
Chapters 4–5: Adoption & Implementation
Technology only creates value when people use it. Tracks implementation from augmentation to autonomy through five maturity levels, with practical guidance on the Help → Automate → Rethink progression and adoption metrics.
Chapter 6: Data & Infrastructure
You can't build AI on messy data. Covers data privacy including the "Lethal Trifecta," AI security and attack vectors, quality controls, and the infrastructure decisions that enable or block AI adoption.
Chapter 7: People & Skills
AI doesn't replace people. It amplifies them. Addresses skill development, empowerment and democratization, organizational structure for AI, and the change management needed to make adoption stick.
Chapter 8: Governance & Ethics
Set guardrails before things go sideways. Covers human-in-the-loop accountability, responsible AI frameworks, ethical considerations, and how to communicate your AI approach to stakeholders and the public.
Chapter 9: Scale & Flexibility
Today's best solution may be obsolete in six months. Covers building for scale while designing for change — including adaptability, technical operations (MLOps), and strategies for graceful deprecation.
Outlook
Chapter 10: The Future of AI
Looking ahead at how AI will reshape work, organizations, and society. Explores the evolving AI landscape and what it means for leaders preparing their organizations for continued change.
Get Notified When the Book Is Available
Leave your email and we'll let you know when the book is ready. No spam — just one notification.
Thank you!
We'll let you know when the book is available.