AI Data Strategy and Governance — Parts I and II

A Practical Enterprise Framework for Building Trusted, Secure, and Responsible AI

This manuscript explains how artificial intelligence evolved from a specialized technical discipline into a general-purpose enterprise capability — and what it takes to convert AI investment into sustainable business value rather than stalled pilots.

Parts I and II cover the AI revolution in the enterprise and the full data strategy stack: architecture, quality, master data, metadata, lineage and provenance — the foundation every governed AI system depends on.

Inside the book

Chapter 1 — The Rise of AI in the Enterprise
Chapter 2 — Understanding Enterprise Data
Chapter 3 — Enterprise AI Strategy
Chapter 4 — Building an Enterprise Data Strategy
Chapter 5 — Enterprise Data Architecture
Chapter 6 — Enterprise Data Quality
Chapter 7 — Master Data Management
Chapter 8 — Metadata Management
Chapter 9 — Data Lineage and Data Provenance

Written for

Chief Data and AI OfficersEnterprise and data architectsAI programme leadersData governance practitioners