As AI adoption accelerates across industries, AI risk management has become essential to ensure trust, compliance, and ethical AI deployment. This book provides a comprehensive guide to identifying, assessing, and mitigating AI risks while aligning with global regulatory standards and best practices.Starting with an introduction to AI risk management, the book explores AI ethics, responsible AI principles, and key challenges, such as bias, fairness, transparency, and security vulnerabilities. It outlines AI risk identification frameworks and strategies for managing data, algorithmic, and operational risks in AI systems.The book delves into the regulatory landscape, covering compliance requirements from frameworks like the EU AI Act, GDPR, and NIST AI Risk Management Framework. It introduces AI governance models and highlights the importance of explainability and transparency in mitigating AI risks.Readers will gain insights into AI risk mitigation techniques, crisis management strategies, and incident response protocols, ensuring resilience against AI failures and adversarial threats.

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