Finance-Grade Data & AI Products
The VANE Loop Framework for Value, Adoption, Navigation & Execution
About the Book
Data & AI products live or die at the intersection of two worlds: the technical reality of what can be built and the financial reality of what creates value. Yet these conversations often happen in parallel rather than together.
Data leaders build business cases without the financial frameworks that boards trust, while finance leaders evaluate Data & AI investments with tools designed for more predictable assets.
Finance-Grade Data & AI Products brings both perspectives into one practical framework. For data and AI leaders, it covers TCO analysis, options pricing for pilots, and how to translate technical progress into financial language. For CFOs and finance leaders, it explains where AI and data connect to capital allocation, risk management, and portfolio governance. We make a case on what makes these investments behave differently from traditional IT and software projects in the enterprise.
The book addresses the technology landscape as per January 2026: AI agents, modern data platforms, and the operational realities they create. We show how existing finance and risk frameworks like COSO need to evolve for systems that behave probabilistically rather than deterministically.
The VANE Loop methodology at the book's core offers a shared system for evaluating value and feasibility together, with continuous checkpoints that keep portfolios honest as assumptions change and reality unfolds.
Whether you're building the business case or approving it, this book gives you the tools to have better conversations and to make better decisions.
Buy NowWhat You'll Learn
A structured journey to deliver on your AI strategy.
AI Outpaces Enterprise Innovation
Why AI compresses timelines in ways that make traditional planning cycles obsolete, and why responding with "more pilots" consumes resources without building capabilities. The real challenge is steering initiatives under fast-changing conditions.
The Vane Loop Methodology
How to align initiatives on value and feasibility, then keep them on course through recurring true-ups and disciplined course correction.
Unit Economics and The Napkin Test
How to define the unit of value for a Data & AI initiative (the atomic outcome that makes or loses money) and build a business case around it that you can explain in 60 seconds, fits on a napkin, and still survives CFO scrutiny.
Risk, Hidden Costs, and Tempo
How to govern probabilistic systems, quantify hidden costs (dual-run, AI debt), and use faster feedback loops to stay ahead of drift.
Feasibility and Maturity
How to assess where your organization actually stands across the maturity dimensions that determine whether execution and adoption will succeed. Includes practical assessment approaches for technology, process, culture, and operational readiness.
CFO Translation and Control Tower Metrics
How to map Data & AI work to P&L language that finance teams recognize and trust. Introduces the "Financial Control Tower," a practical set of metrics for steering a Data & AI portfolio with the same rigor applied to other capital investments.
About the Authors
Meet the experts behind the Vane Loop methodology.
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