Foundations of AI Governance and Ethical Risk Management

As artificial intelligence rapidly integrates into modern business operations, establishing guardrails is no longer optional—it is a core business requirement. Understanding how to deploy AI responsibly ensures safety, compliance, and public trust. This course guides you through the essential concepts of AI ethics, risk management, and regulatory compliance. You will transition from understanding basic ethical dilemmas to actively identifying bias, evaluating transparency, and applying modern governance frameworks to real-world business scenarios. What you'll learn: - Understand foundational AI ethics principles, including fairness, accountability, and transparency. - Identify and mitigate bias in datasets, machine learning models, and generative AI outputs. - Navigate modern compliance standards, including international regulations and risk management frameworks. - Establish responsible AI workflows within organizational structures to manage deployment risks. - Analyze real-world ethical dilemmas through structured, written case studies and scenarios. You will start by mastering core terminology and historical context before moving on to practical risk assessment methodologies and compliance guidelines. The course concludes with written exercises designed to help you draft your own organizational AI policy. This course is designed for beginners, business professionals, policy makers, and product managers who want to understand the ethical implications of AI with no prior technical or coding experience required. Start reading today to build a solid foundation in responsible AI leadership.