AI Identities

AI Identities introduces a groundbreaking concept: AI Agents should be recognized and governed as a new class of identity within enterprise environments. As artificial intelligence evolves from predictive models to autonomous agents with memory, goals, and tool access, enterprises face a new spectrum of identity risk that transcends traditional IAM frameworks. This book lays out the philosophical, architectural, and operational foundations necessary to govern these intelligent machine identities across their lifecycles.

Structured across six parts, the book begins by grounding readers in identity security and ownership. It then introduces the concept of AI agents as complex, evolving identities that demand governance, not just access control. It offers practical guidance on lifecycle management, trust, discovery, and incident response for AI agents, and concludes with future-facing perspectives on human-AI collaboration, critical infrastructure, and compliance.

This is not a coding manual or abstract ethics bookit's a field guide for security professionals, architects, and digital leaders who must design, secure, and take responsibility for the AI identities acting on behalf of their organizations. The writing is crisp, deeply informed, and structured to support real-world decision-making in an era where the lines between automation and agency are quickly disappearing.

WHAT YOU WILL LEARN:

• Understand the emerging category of AI Identities and how they differ from traditional machine accounts.
• Develop strategies for ownership, governance, and lifecycle control of AI agents in enterprise environments.
• Build a framework for discovery, trust scoring, explainability, and behavioral auditing of autonomous agents.
• Learn how to respond to security incidents involving intelligent agents and prevent cascading failures.

• Gain insights into the future of human-AI collaboration and the governance challenges posed by agentic AI.
  WHO THIS BOOK IS FOR

  This book is for enterprise security architects, identity professionals, risk officers, and technology executives responsible for the governance and security of digital systems. It is written to inform decision-makers and practitioners who need to understand how to integrate AI agents into their existing identity, compliance, and security programs.

  The first comprehensive framework for governing AI agents as a new category of identity Combines strategic vision with actionable guidance tailored to enterprise security professionals Tackles ownership, control, and lifecycle governance of autonomous systems head-onbefore regulations mandate it

  Autorentext

Rosario Mastrogiacomo is the Chief Strategy Officer at SPHERE, a cybersecurity firm specializing in identity hygiene and data governance. With three decades of experience in the field, Rosario leads initiatives that blend strategy, innovation, and AI to solve some of the most pressing identity security challenges. He is a recognized speaker, thought leader, and host of the podcast Smells Like Identity Hygiene, where he explores the intersections of cybersecurity, automation, and human responsibility. Rosario is also the author of widely circulated industry articles and a contributor to executive-level conversations around the role of AI in enterprise identity and risk management.

Inhalt

PART 1: Identity Security 11.- Chapter 1: The New Actors- Chapter 2: Understanding Identity Security (Primer) .- Chapter 3. Introducing AI Identities Automation Reimagined.- Chapter 4: Identity HygieneFoundations for Securing All Identities.- PART 2: Identity Security and AI.- Chapter 5. Ownership as a Security Control.- Chapter 6. What AI Agents Really Are AI Identities and the Case for a New Category.- Chapter 7: The Evolution of Identity Governance.- Chapter 8: Technical Implementation of AI Identity Governance.- Chapter 9: Delegation, Authority, and the Risk of Agent Autonomy.- PART 3: Securing AI Agents with RAISE.- Chapter 10: The RAISE Framework for Governing AI Identities.- Chapter 11:REVEAL - Discovery and Inventory of AI Identities.- Chapter 12: ASSIGN - Ownership in the Age of AI.- Chapter 13: INTERPRET - Trust, Explainability, and AI Agent Reputation.- Chapter 14: SECURE - Building Resilience into AI Identity Lifecycles.- Chapter 15: EVALUATE - The Lifecycle of an AI Identity.- PART 4: Governance, Controls, and Risk Management.- Chapter 16: Navigating Complex Regulatory and Compliance Frameworks for AI Identities.- Chapter 17: Inherited Risk Managing Third-Party AI Identities in the Supply Chain.- Chapter 18: Malicious Use and Insider Threats in AI Identity Systems.- Chapter 19: When AI Goes Off Script Real-World Agentic AI Failures.- Chapter 20: Cognitive Instability in AI Agents Security Risks from Misjudgment, Hallucination, and Drift.- Chapter 21: Ethical Considerations and Responsible AI Governance.- PART 5: Resilience and Response.- Chapter 22: Security Controls and Countermeasures for AI Identities.- Chapter 23: Incident Response and Resilience for AI Identities.- Chapter 24: Forensics for AI Identities.- Chapter 25: AI Identities in Critical Infrastructure.- Chapter 26: Building a Lifecycle for AI Identity Management.- Chapter 27: Operationalizing AI Identity Governance A CISO's Playbook.- PART 6: Looking Ahead.- Chapter 28: Futureproofing and Strategic Roadmaps for AI Identity Governance.- Chapter 29: The Future Role of the Identity Architect.- Chapter 30: Human-AI Collaboration and the Future of Work.