Abstract
This commentary examines how GenAI can meaningfully augment qualitative management accounting research while requiring careful alignment with researchers' epistemological commitments. Contrasting interpretive and positivist traditions across research design, data collection, analysis, and writing, we critically examine opportunities – including scaling interviews, generating AI-created vignettes, real-time interview augmentation, and using AI to systematically challenge emerging interpretations. We also draw attention to two less obvious methodological risks. First, because GenAI generates outputs by modelling statistical regularities in large-scale textual corpora, its unreflective use may orient analysis toward surface patterns and apparent consistencies, thereby silently introducing assumptions of stability and generalisability into traditions that prioritise situated meaning, process, and context. Second, delegating core activities such as interpretive analysis or writing to AI may lead scholars to forgo the generative "struggles" through which qualitative insight typically crystallizes. We conclude that GenAI can have a legitimate role in qualitative management accounting research, but the risks call for deliberation, reflexivity, and transparency.