IT leaders on the secure deployment of internal AI chatbots and knowledge automation tools within an organization. It emphasizes that while these tools offer significant productivity benefits, they pose serious risks, including data exfiltration, prompt injection attacks, and compliance violations (especially for regulated industries like healthcare and finance). To mitigate these dangers, the text advocates for implementing specific architectures like Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP), which keep sensitive corporate data separate from the AI model's training process and enforce strict access controls. The guide then outlines a six-phase step-by-step approach covering governance definition, technology selection, data protection measures, access control integration, continuous monitoring, and user training to ensure safe and effective adoption. ... Read More