What you'll learn

AI adoption can outpace organizational accountability, risk assessment, policy development, and compliance controls. In this course, AI Governance, Risk, and Compliance for CompTIA SecAI+, you'll gain the ability to explain how organizations govern AI, evaluate AI-related risks, and align AI use and development with regulatory, standards, and corporate requirements. First, you'll explore organizational structures that support AI governance, including an AI Center of Excellence and AI policies and procedures. You'll also distinguish the responsibilities of data scientists, AI architects, machine learning engineers, platform engineers, MLOps engineers, AI security architects, AI governance engineers, AI risk analysts, AI auditors, and data engineers. Next, you'll examine responsible AI principles such as fairness, reliability and safety, transparency, privacy and security, differential privacy, explainability, inclusiveness, accountability, consistency, and awareness training. You'll connect these principles to risks involving bias, accidental data leakage, reputational loss, model accuracy and performance, intellectual property, autonomous systems, and shadow AI. Finally, you'll learn how compliance affects the business use and development of AI. You'll review the European Union AI Act, Organisation for Economic Co-operation and Development standards, International Organization for Standardization AI standards, the National Institute of Standards and Technology AI Risk Management Framework, corporate policies, third-party compliance evaluations, and data-sovereignty requirements. When you're finished with this course, you'll have the skills and knowledge of AI governance, risk, and compliance needed to explain governance structures, evaluate AI risks, interpret compliance obligations, and prepare for Domain 4.0 of the CompTIA SecAI+ CY0-001 certification exam.