INSIGHTS
The AI Book of Knowledge (AIBOK) is a six-volume series for leaders, practitioners, students and researchers. It explains enterprise AI strategy, architecture, economics, governance, workforce transformation and the AI-native enterprise.
Six volumes connect strategy, technology, finance, governance, organization and transformation into one practical framework for managing enterprise intelligence and measurable business value.
AI BOOK OF KNOWLEDGE (AIBOK)
Six-Volume Enterprise AI Framework
A practical series for executives, architects, finance leaders, governance professionals, educators and researchers managing AI as an enterprise capability.
Managing Enterprise AI: Foundations, Strategy & Enterprise AI Management
Volume 1 establishes enterprise AI as a managed business capability. It covers strategy, operating models, opportunity selection, maturity assessment, executive accountability and value measurement, helping leaders move beyond isolated pilots toward coordinated roadmaps, measurable outcomes and sustainable enterprise value.
Enterprise Generative and Agentic AI Architecture
Volume 2 explains how generative and agentic AI moves safely into production. It covers enterprise architecture, gateways, model portfolios, RAG, agent autonomy, observability, evaluation, security and optimization, with practical guidance for controlling technical complexity while connecting system performance to business outcomes.
AI Economics and Financial Management
Volume 3 creates a financial discipline for enterprise AI. It covers FinOps, total cost of ownership, unit economics, variable consumption, forecasting, budgeting, showback, chargeback, portfolio investment and accounting, giving finance and technology leaders a shared language for responsible AI spending.
Enterprise AI Governance, Risk, Security and Responsible AI
Volume 4 presents governance as a continuous operating capability. It connects decision rights, risk management, responsible AI, transparency, explainability, cybersecurity, resilience, incident management, auditability and regulatory readiness, showing how proportionate controls become practical evidence and trusted enterprise operations.
Organizing for Enterprise AI: Operating Models and Value Realization
Volume 5 focuses on the people and operating models required to realize AI value. It covers accountability, centers of excellence, human-AI collaboration, workforce redesign, reskilling, adoption, change management, performance measurement and continuous improvement after systems are technically deployed.
The AI-Native Enterprise and Enterprise Intelligence Management
Volume 6 explores the AI-native enterprise and the evolution toward Enterprise Intelligence Management. It covers maturity, transformation sequencing, multi-year roadmaps, shared human and machine intelligence, performance measurement and emerging agentic organizations, creating a practical foundation for long-term intelligent business transformation.