Overview

In the age of AI-augmented work, the organizations that win are those that can surface the right knowledge at the right moment not just to individual employees, but to intelligent systems acting on their behalf. Yet for most enterprises, the majority of their institutional intelligence remains locked inside unstructured documents, disconnected SharePoint libraries, fragmented email threads, and siloed line-of-business applications. Microsoft 365 Copilot promises to change this but only when the underlying knowledge infrastructure is deliberately engineered to support it. Internal Knowledge Systems with Microsoft 365 Copilot is a comprehensive, practitioner-focused technical guide written for enterprise architects, AI engineers, SharePoint administrators, and Microsoft 365 power users who need to build, optimize, and govern AI-powered knowledge workflows at scale. From the foundational principles of Retrieval-Augmented Generation (RAG) to the cutting edge of autonomous knowledge agents, this book equips you with the architectural patterns, configuration strategies, and engineering techniques required to transform your Microsoft 365 tenant into a high-fidelity organizational intelligence platform. You will learn how to design SharePoint taxonomies and metadata schemas that make your content machine-readable, build end-to-end RAG pipelines using Azure AI Search and Copilot Studio, extend Copilot with OpenAPI plugins and declarative agents, and engineer semantic retrieval systems that return accurate, contextually grounded responses. Deep dives into Microsoft Graph API, Azure AI Document Intelligence, sensitivity labels, and compliance-aware retrieval ensure that your implementations are not only performant but also secure and audit-ready. Each of the fifteen chapters builds progressively on the last from knowledge architecture fundamentals through advanced evaluation frameworks and organizational change management giving you both the conceptual depth and the hands-on implementation guidance needed to deliver measurable results. Real-world patterns, configuration walkthroughs, and decision frameworks ensure that every concept maps directly to enterprise scenarios you can act on immediately. Whether you are architecting a Copilot deployment from scratch, troubleshooting poor retrieval quality, or making the case to leadership for AI knowledge investment this book is your definitive field guide. Start building the knowledge infrastructure your organization deserves. Your Copilot is only as good as the knowledge you give it.

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