Auditing Artificial Intelligence: Risk, Security, and AI Tools

As organizations rapidly adopt artificial intelligence, auditors must understand how to evaluate AI risks, secure these systems, and use AI tools responsibly. This text-based course provides a clear foundation in AI auditing, cybersecurity implications, and generative AI governance. You will transition from a traditional auditor or IT professional to someone who can confidently assess AI implementations. You will understand how to apply structured risk management frameworks, identify security vulnerabilities unique to AI, and ethically integrate generative tools like ChatGPT into your daily audit workflows. What you'll learn: Understand foundational AI concepts, machine learning basics, and the core components of AI systems; Evaluate AI risks using modern frameworks, including standard AI risk management and governance models; Analyze cybersecurity vulnerabilities specific to AI, such as data privacy leaks and model manipulation; Apply prompt engineering techniques to safely automate audit testing and documentation with generative AI tools; Assess data governance practices to ensure compliant, unbiased, and high-quality inputs for AI models; Design structured audit plans tailored for machine learning pipelines and automated decision-making systems. The training begins with essential terminology and the fundamentals of AI technologies before guiding you through risk assessment frameworks, security protocols, and practical generative AI use cases. You will read conceptual explanations and work through written scenarios to reinforce your skills. This course is designed for beginner auditors, IT professionals, risk managers, and compliance officers who want to build a solid foundation in AI auditing without needing a background in coding or advanced statistics. Start reading today to prepare your auditing skillset for the era of artificial intelligence.