ENTERPRISE AI RELIABILITY ENGINEERING: Operationalizing Trust, Governance, Testing, and Autonomous Systems at Scale

Enterprise AI Reliability Engineering Operationalizing Trust, Governance, Testing, and Autonomous Systems at ScaleArtificial Intelligence is transforming the enterprise at an unprecedented pace. Organizations are deploying Generative AI, Retrieval-Augmented Generation (RAG), copilots, autonomous agents, and multi-agent systems to drive productivity, innovation, and business value.Yet one critical challenge remains: Can AI Be Trusted?As enterprises move beyond experimentation and into large-scale adoption, reliability becomes the defining factor for success. Hallucinations, governance gaps, unpredictable behavior, security risks, and autonomous decision-making create new challenges that traditional engineering and operational models were never designed to address.Enterprise AI Reliability Engineering introduces a practical framework for building, governing, testing, observing, and operating trustworthy AI systems at enterprise scale.Inside this book, you'll learn how to: - Establish AI reliability and trust frameworks- Build reliable RAG and knowledge-grounded AI systems- Implement AI evaluation, testing, and regression engineering- Govern Agentic AI and autonomous systems responsibly- Design observability and monitoring for AI operations- Manage AI risks, failures, and reliability at scale- Create enterprise operating models for sustainable AI adoptionDrawing from proven engineering principles and real-world enterprise practices, this book introduces the emerging discipline of Enterprise AI Reliability Engineering (EAIRE)-a structured approach that combines quality engineering, reliability engineering, governance, observability, operations, and trust engineering into a single operating model.Whether you are a CIO, CTO, AI Leader, Enterprise Architect, Quality Engineering Professional, Product Leader, Governance Executive, or Transformation Leader, this book provides the frameworks and practical guidance required to move AI from experimentation to enterprise-scale adoption with confidence.The Future of AI Is Not Defined by Intelligence Alone.The future belongs to organizations that can operate AI reliably, safely, transparently, and at scale.Trust Must Be Engineered.

Pagina's: 334, Paperback, Independently published