Artificial intelligence has moved beyond experimentation and into the core of enterprise operations. Generative AI and agentic systems are increasingly embedded in customer experiences, business processes, decision-making workflows, and enterprise platforms, introducing new levels of autonomy and complexity. As organizations accelerate AI adoption, traditional security and governance approaches, designed for deterministic software and clearly defined system boundaries, are proving inadequate. Enterprise leaders now manage systems that are probabilistic, adaptive, and capable of acting independently across data, applications, and business processes.

This book examines AI security through an enterprise lens, focusing on the governance, architectural, operational, and risk-management challenges that emerge when AI becomes part of critical business functions. Drawing on real-world experience across highly regulated industries, it explores how organizations can establish trust, accountability, resilience, and control in AI-enabled environments. Rather than treating AI security as a model-centric problem, the book frames it as an enterprise decision-making challenge—one that spans architecture, governance, identity, compliance, operational oversight, and organizational accountability. Through practical frameworks and case studies from financial services, healthcare, logistics, insurance, retail, and technology sectors, readers will learn how to secure AI systems at scale while balancing innovation, regulatory expectations, and business value.

You Will Learn

• Develop enterprise-wide strategies for securing generative and agentic AI systems across governance, architecture, operations, and compliance.
• Identify and mitigate emerging risks related to autonomous decision-making, delegated authority, data access, and AI-enabled business processes.
• Design security, trust, and governance frameworks that support responsible AI adoption in complex and regulated enterprise environments.

This Book Is For

Enterprise architects, Security architects, CISOs, AI governance leaders, risk and compliance professionals, technology executives, and senior decision-makers responsible for deploying, governing, and securing AI systems at enterprise scale.

Hitender Saxena is an Associate Director and Lead Technologist, and he serves as Global AI Security Lead and GDS Emerging Technology Security & Innovation Leader. With over two decades of experience in cybersecurity architecture, cloud security, and emerging technology risk management, his work is focused on defining security approaches for AI-enabled platforms and enterprise technology environments at scale.

His professional experience spans cloud infrastructure security, enterprise cybersecurity architecture, AI governance, and secure digital transformation across industries, including financial services, insurance, manufacturing, and transportation. He has contributed to industry analyst engagements with IDC on cloud security in the era of artificial intelligence and with Forrester on AI security, enterprise cyber defence, and emerging technology governance. He has represented cybersecurity perspectives on AI adoption and security governance at the India AI Summit.

He holds the TOGAF Enterprise Architecture certification, Microsoft Azure Solutions Architect Expert, AWS Certified Solutions Architect, Microsoft Azure Security Engineer Associate, AI Engineer Associate, the Certificate of Cloud Security Knowledge (CCSK) from the Cloud Security Alliance, and an Internet of Things Fundamentals credential from Stanford University. He holds an MBA in Information Technology.