Governing Generative AI Data: Security, Privacy, and Compliance

As generative AI tools become integrated into daily workflows, organizations face unprecedented risks regarding data privacy, intellectual property, and compliance. Managing these risks requires a modern approach to data governance tailored specifically for AI-driven technologies. This text-based course equips you with the fundamental knowledge to establish guardrails, secure sensitive data, and maintain regulatory compliance when adopting generative AI. You will learn how to identify data leakage risks, implement privacy-by-design, and set up clear internal policies. What you'll learn: - Understand foundational data governance principles tailored specifically for generative AI models. - Identify and mitigate risks associated with data leakage, shadow AI, and prompt injection. - Implement privacy-by-design strategies to comply with modern data protection regulations. - Establish secure data pipelines for retrieval-augmented generation (RAG) and vector databases. - Create clear organizational policies for safe AI usage and intellectual property protection. Starting with core definitions and security concepts, the course guides you through practical risk assessment frameworks and policy templates, all explained through clear, written case studies and scenarios. This course is designed for business leaders, compliance officers, IT professionals, and beginners looking to understand the intersection of data governance and artificial intelligence, with no prior technical background required. Read through our comprehensive guides and start building a secure foundation for AI adoption today.