Create AI-ready enterprise solutions with MongoDB and discover how to design intelligent architectures that transform data into innovation, efficiency, and real business value Key Features Complete guide covering GenAI to agentic AI, semantic protection to multi-agent systems - 25+ proven AI use cases delivering measurable impact across 6+ industries - 15+ real enterprise case studies from Novo Nordisk, Base 39, and more - Purchase of the print or Kindle book includes a free PDF eBook Book Description AI is reshaping industries, yet most organizations struggle to scale beyond pilots. Architectures for the Intelligent AI-Ready Enterprise bridges this gap with practical frameworks for building AI-ready architectures that deliver lasting business value. The book helps you explore System of Action databases and see why they're revolutionizing real-time decision-making. Through real-world applications across industries, from manufacturing and healthcare to financial services and retail, you'll discover how leading organizations transform their operations. You'll learn semantic data protection techniques that enable AI in regulated industries, as well as master advanced patterns including agentic AI and multi-agent orchestration. Written by MongoDB and industry practitioners, this book combines strategy with technical depth and proven business value. You’ll modernize by enabling AI innovation while preserving existing investments, implement trustworthy AI with governance frameworks, and build scalable solutions using a unified data platform like MongoDB that delivers measurable ROI and transformation. Whether you're architecting next-generation systems or modernizing legacy infrastructure, this book provides the patterns, case studies, and expert guidance to build enterprises that’ll thrive in an intelligent future. What you will learn Design AI-ready data architectures that scale in production - Define systems of action and explain why they matter for enterprises - Modernize legacy systems for AI-ready, unified architectures - Implement governance, privacy, and compliance frameworks for AI - Explore real-world AI implementations for over six industries - Deploy production RAG and agentic systems with MongoDB - Apply semantic data protection in regulated industries - Build domain-specific AI agents and intelligent copilots - Apply MCP, causal AI, and multi-agent systems for future-ready architectures Who this book is for This book is for IT leaders, enterprise architects, solution designers, and innovators ready to transform AI potential into production reality. Whether you're modernizing legacy systems, implementing scalable AI solutions, or translating AI concepts into measurable business outcomes, this book provides practical frameworks and industry-proven patterns. Basic familiarity with enterprise systems and data architecture is helpful, but deep AI expertise isn't required. Table of Contents AI Modernization to Innovation - What Sets GenAI, RAG, and Agentic AI Apart - The System of Action - Trustworthy AI, Compliance, and Data Governance - Modernization Using AI - Practical Applications of Agentic and GenAI in Manufacturing – Part 1 - Practical Applications of Agentic and GenAI in Manufacturing – Part 2 - AI-Driven Strategies for Media and Telecommunication Industries - Cognigy's Voice and Chatbots in the Time of Agentic AI - Harnessing AI to Transform the Retail Industry - Financial Services and the Next Wave of AI (N.B. Please use the Read Sample option to see further chapters) “After building Iguazio to help enterprises operationalize (Gen) AI applications and agents, I've seen firsthand the challenges of scaling and deploying AI and managing ethical, security and compliance risks. This book tackles exactly that challenge. From RAG architectures to AI factories to agentic workflows, it provides the blueprints we wish existed years ago. The partnership examples with MongoDB show how unified platforms and data management accelerate real business outcomes. A must-read for anyone turning AI strategy into results.” Asaf Somekh, Co-Founder & CEO of Iguazio, a McKinsey Company “Building AI that actually works in production requires understanding the full stack—not just models, but data architecture, orchestration, and operational considerations. This book provides that view with real examples and honest assessments of what's hard. The cross-industry case studies helped our customers make infrastructure and realistic deployment pattern decisions for enterprise AI.” Shaunak Godbole, Field CTO at Fireworks AI Boris Bialek has worked in the IT industry since the 1990s and was one of the initial drivers of Linux in Europe, delivering the first SAP port to Linux, conducting the first benchmarks, and securing the first clients. Since then, he has led product and development teams across IBM and FIS, driving innovation for both the end product and development productivity. Boris Bialek joined MongoDB in 2019, igni