Case study research demands careful boundary-setting, rich contextualisation and a defensible chain of evidence. This paper shows how generative AI can support that work — while transparency, theoretical grounding and researcher oversight preserve the rigour that qualitative case studies require. Together with the AI-assisted thematic analysis paper, it forms a complete published toolkit for AI-supported qualitative research: the case study process shapes the research design, and the six-step AI process analyses the data it produces.

The same principles carry across both papers: give the AI the research aim, questions, context, participants and theoretical underpinnings before it works; instruct it step by step rather than in one request; evaluate its outputs against published criteria; and document every prompt so the process is transparent and auditable.