Interpreting Qualitative Data with AI: Potentials and Pitfalls

Описание: Speakers:
Catherine Welch (Trinity College Dublin)
Duc Nguyen (Manchester)

We'll discuss the proposed use of GenAI models for qualitative data analysis. In Part 1, we examine the current excitement about the use of GenAI for qualitative data analysis. This has been fuelled by the release of ‘qualAI’ tools by a range of commercial providers, who promote the allure of increased efficiency, productivity and instant insights. Techno-optimistic narratives have also been a feature of much of the discussion around (Gen)AI in management journals. In Part 2 of the presentation, we turn to the perils of using GenAI for qualitative research. We problematise the deliberate act of placing a generative AI model between a qualitative researcher and their data, arguing that it displaces and distorts the practice of qualitative data analysis, as well as posing a potential threat to research integrity. In Part 3, we turn to what we see as the potential of this historical moment.

Suggested readings:
Bechky, B. A., & Davis, G. F. (2024). Resisting the Algorithmic Management of Science: Craft and Community After Generative AI. Administrative Science Quarterly, 70(1), 1-22.
Jowsey, T., Braun, V., Clarke, V., Lupton, D., & Fine, M. (2025). We reject the use of generative artificial intelligence for reflexive qualitative research.
Nguyen, D. C., & Welch, C. (2025). Generative Artificial Intelligence in Qualitative Data Analysis: Analyzing—Or Just Chatting? Organizational Research Methods, 0(0)
Nguyen, D. C., & Welch, C. (2025). Engaged and Responsible Scholarship: Why Qualitative Researchers Should Not Embrace GenAI. Business & Society. 0(0)