The rapidly improving capabilities of large language models (LLMs) create both opportunities and threats for professions.Organizational scholars have been quick to raise the alarm about the perils that generative artificial intelligence (AI) poses for society and academic scholarship in general (Lindebaum et al., 2025) and qualitative research in particular (Nguyen & Welch, 2026).Any technology that is as powerful as LLMs inevitably will create unintended and unforeseen negative consequences; for example, chatbots allow users to rapidly create shallow qualitative analyses, made-up quotes, and bogus theory.However, critics often ignore a central argument in technology studies: The impact of any technology depends on the social practices in which it is embedded.What is our alternative, really?Knowledge work is rapidly changing across professional groups.Lawyers, physicians, and engineers now increasingly use generative AI to improve the quality and speed of their work.Can management scholars decide to sit this out?Proponents of an artisanal anti-AI culture may seek to stigmatize the use of LLM-based tools to aid research, discouraging and punishing AI use.This would leave our profession, tasked to educate future managers, illprepared to understand AI-augmented knowledge work.Because craft and community are invaluable to our profession (Bechky & Davis, 2025), we should engage in practice development around AI or we risk becoming obsolete in the eyes of external stakeholders on whom we depend.At best, AI provides qualitative researchers with a pedagogic opportunity in the same way that business analytics provided earlier for statisticians.Our expertise can inform "lay qualitative research" conducted across the private and public sectors by millions of white-collar workers.In this essay, I will focus solely on qualitative analysis, although AI can support many parts of the research process. LLMs in Qualitative AnalysisLLMs are based on the transformer algorithm that effectively captures complex interaction patterns in data, such as semantic meanings in sentences and paragraphs.The technology became widely known with ChatGPT, and many still view "GenAI models . . .as a type of chatbot" (Nguyen
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