Agentic AI is rapidly transforming how organizations build robust, adaptive security postures that respond dynamically to evolving threats. AI-enhanced AWS services are also making it easier to govern, document, share, and operationalize data in an organization. By the end of this chapter, you’ll understand how to confidently implement the three core pillars of data governance: ensuring appropriate data discovery and access, maintaining comprehensive security protections, and implementing robust audit capabilities. I’ll guide you through the AWS Shared Responsibility Model so you can clearly distinguish between AWS’s infrastructure security obligations and your application-level security responsibilities. You’ll learn to implement enterprise-grade security using AWS IAM, key management service, and certificate manager. I then explore the unique security challenges introduced by generative AI solutions and how best to mitigate them. We’ll examine Model Context Protocol (MPC) security considerations, as MCP’s ability to connect agentic AI with enterprise systems creates both opportunities and risks that require careful management. This foundation will enable you to build AI-augmented data solutions that deliver transformative business value while maintaining the security standards that enterprises demand.