AI Risk Management and Incident Response Essentials

As artificial intelligence becomes central to modern business, organizations face unprecedented security, ethical, and operational risks. Understanding how to proactively identify vulnerabilities and respond to AI-specific incidents is now a critical skill for tech and business professionals. This written course guides you through the foundational concepts of AI risk management, helping you transition from a beginner to a practitioner capable of securing AI deployments. You will learn to evaluate risks associated with machine learning models, large language models, and automated decision systems. What you'll learn: - Understand core AI risk frameworks, including modern standards like the NIST AI Risk Management Framework. - Identify common AI vulnerabilities, such as data poisoning, model evasion, and prompt injection. - Establish structured incident response plans tailored specifically to AI system failures and security breaches. - Apply ethical guidelines and compliance strategies to mitigate bias and ensure algorithmic fairness. - Configure monitoring strategies to detect model drift and anomalous behavior in production. The course begins with essential terminology and governance frameworks before moving into practical risk assessment methodologies and step-by-step incident response workflows. You will work through written scenarios and conceptual exercises designed to reinforce your learning. This course is designed for IT professionals, risk managers, and beginners looking to enter the field of AI governance, with no prior cybersecurity or advanced programming experience required. Start reading today to build safer, more resilient AI systems for your organization.