Practical Agentic AI Governance, Compliance, and Runtime Security

Deploying AI agents is no longer the hardest part.
Keeping them governed, compliant, observable, and secure in production is.
As organizations rapidly adopt autonomous agents, multi-agent systems, and AI-powered workflows, many discover that traditional governance and security models were never designed for systems that can make decisions, invoke tools, access sensitive data, and collaborate with other agents autonomously.
How do you enforce policies at runtime?
How do you maintain continuous compliance across thousands of agent actions?
How do you create audit trails that satisfy regulators, security teams, and enterprise stakeholders?
How do you detect and contain risky agent behavior before it becomes a business problem?
Practical Agentic AI Governance, Compliance, and Runtime Security provides a hands-on blueprint for building governance and runtime protection capabilities that work in real-world enterprise environments.
Rather than focusing on theory, this book shows you how to implement governance controls, compliance automation, runtime policy enforcement, observability pipelines, audit frameworks, and operational security mechanisms that can scale across modern AI platforms.
Inside, you will learn how to:

• Build governance control planes for autonomous agents and multi-agent systems
• Implement policy-as-code using modern authorization and policy frameworks
• Establish continuous compliance programs aligned with leading industry standards
• Create immutable audit trails and enterprise-grade traceability pipelines
• Deploy runtime guardrails and enforcement mechanisms for agent actions
• Monitor agent behavior and detect anomalies in real time
• Integrate governance and compliance controls into CI/CD workflows
• Automate evidence collection, reporting, and audit preparation
• Build incident response and recovery procedures for agent-driven environments
• Scale governance programs across cloud, hybrid, and multi-tenant architectures