Generative AI presents a transformative opportunity to address the knowledge and skill gap in mainframe environments, particularly for Db2 for z/OS. By leveraging large language models (LLM) and Retrieval–Augmented Generation (RAG) patterns, organizations can create intelligent systems that make mainframe expertise more accessible and actionable. When integrated with automation frameworks, these solutions not only simplify complex workflows for early tenure DBAs —reducing the steep learning curve—but also enable experienced DBAs to focus on strategic, high–value tasks. This session explores how generative AI can be applied to enhance mainframe productivity, preserve institutional knowledge, and create a scalable foundation for skills development across diverse user groups.
