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Home > Computing and Information Technology Books > Computer Science Books > Artificial intelligence > Expert systems / knowledge-based systems > Enterprise Knowledge Intelligence: Strategy, Architecture & AI-Powered Discovery for Humans and Machines
Enterprise Knowledge Intelligence: Strategy, Architecture & AI-Powered Discovery for Humans and Machines

Enterprise Knowledge Intelligence: Strategy, Architecture & AI-Powered Discovery for Humans and Machines


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About the Book

95% of enterprise AI pilots fail - not because the models are wrong, but because the knowledge underneath them is ungoverned, unstructured, and invisible to both humans and machines.

Your employees spend 2.5 hours every day searching for answers that already exist. Your AI agents retrieve stale data and make confident wrong decisions. Your Salesforce bot gives a different answer than your Teams assistant - both drawing from the same organisation.

This is the Knowledge Problem. Every enterprise has it. Almost none have solved it for both their human employees and their machine consumers simultaneously.

Enterprise Knowledge Intelligence is the blueprint that fixes this - permanently.

Written for Heads of Engineering, Managing Directors, Distinguished Architects, and Product Managers, this second edition introduces the Knowledge Fabric: a governed, AI-native architecture that delivers the Five Rights of Enterprise Knowledge Discovery - the right information, to the right person, at the right time, in the right context, in the right format - for every employee asking a question through Teams and every Salesforce agent calling a Knowledge API.

What you will build across eight chapters and eleven appendices:

→ A business case with quantified ROI for both human and machine knowledge consumers

→ A complete map of your enterprise knowledge universe - including the structured data, conversation history, and engineering codebases that most organisations never govern

→ A five-tier governance and classification framework that supports machine-readable formats, machine consumer identity, and full regulatory alignment across GDPR, EU AI Act, HIPAA, SOX, and FCA

→ The seven-layer Knowledge Fabric architecture with a full Knowledge API specification (OpenAPI 3.0) for agentic and application consumers

→ Intent-based discovery patterns for seven consumer types - from the frontline employee to the autonomous AI agent - including MCP and A2A integration

→ Reference architectures for AWS (Bedrock KB + Neptune Analytics GraphRAG + AgentCore), GCP (Gemini Enterprise + AlloyDB AI + Spanner Graph), and Azure (AI Search + Foundry IQ + Copilot Studio), plus a cost comparison across 1 million queries per month

→ A four-phase roadmap from eight-week POC to enterprise scale, with nine quick wins, a dual ROI framework, and a four-level Knowledge Fabric Maturity Model

→ Eleven production-ready appendices: governance checklists, POC scorecards, persona templates, KPI dashboards, integration pattern catalogs, and a 20-question maturity self-assessment

Grounded in 95+ primary sources from 2024-2026, every chapter builds on the last - from strategy and governance through architecture, cloud deployment, and execution. Fifty original data tables and framework figures make the concepts immediately applicable to your organisation's technology stack and regulatory environment.

The central thesis of this book: the era of human-only knowledge management architecture is over. The platform that satisfies the Five Rights for the employee and the AI agent simultaneously is the platform that wins - in productivity, in AI ROI, and in competitive advantage.

The knowledge exists. The technology exists. The governance frameworks exist.

What this platform needs now is the leader who decides to build it.


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Product Details
  • ISBN-13: 9798199292672
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 279 mm
  • No of Pages: 170
  • Returnable: N
  • Sub Title: Strategy, Architecture & AI-Powered Discovery for Humans and Machines
  • Width: 216 mm
  • ISBN-10: 8199292679
  • Publisher Date: 26 Jun 2026
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 9 mm
  • Weight: 408 gr


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