City Research Online

Abstract

The field of management and organizational research is experiencing a significant transformation fueled by the integration of artificial intelligence (AI) technologies and the abundant data generated from diverse sources. While AI deployment presents opportunities for systematic and rigorous scholarly inquiry, it also poses an ontological challenge for theory building in understanding the organizational world. This paper addresses the need for actionable methodological guidance by exploring the intersection of AI and qualitative research in management and organizational studies. First, we review the utilization of natural language AI (NL-AI) techniques, focusing on three main forms: assistive AI, interpretive AI, and generative AI, and their role in research, intervention level and explorative quality. Second, we propose an AI-ductive model that integrates human interpretation with the capabilities of AI facilitating holistic data exploration for theory building and moving beyond the understanding of AI as a toolbox. This paper contributes to advancing the debate on how to foster knowledge generation in qualitative management and organizational research by leveraging AI attending to the hermeneutical circle and the intersection between AI and the researcher as co-producers of knowledge.

Publication Type:	Conference or Workshop Item (Paper)
Publisher Keywords:	artificial intelligence; hermeneutic circle; theory building; natural language AI
Departments:	Bayes Business School > Management

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