How AI, RAG, and Agents Transform Mainframe Operations

General-purpose LLMs often give inaccurate answers for mainframe-specific queries because they lack domain-grounded knowledge. Retrieval-Augmented Generation (RAG) addresses this by ingesting mainframe documentation, best practices, and client-specific content to produce more accurate, relevant responses. Layering agentic AI on top enables automation of operational tasks such as health checks, workload optimization, service desk ticket creation, and hybrid cloud integration, making mainframe operations more efficient and accessible to newer professionals.