Artificial Intelligence in Qualitative Research: Insights From Experts via Reflexive Thematic Analysis

The rapid advancement of artificial intelligence (AI) is increasingly shaping research methodologies across disciplines. However, its integration in qualitative research remains controversial due to epistemological, ethical, and human-centered concerns. This study explores the perspectives of 14 expert qualitative researchers from socio-anthropological and healthcare fields working in Italian academic and hospital settings, with a focus on the opportunities, challenges, and future directions of AI use in qualitative inquiry. Through semi-structured interviews and reflexive thematic analysis, four main themes were developed. First, participants expressed ambivalent attitudes-balancing curiosity with technophobia and emphasizing the need for human oversight and contextual interpretation. Second, an anthropological and philosophical dimension was constructed, underscoring the importance of reflexivity, creativity, and researcher identity as essential counterbalances to AI's mechanistic tendencies. Third, researchers acknowledged AI's practical benefits in tasks such as transcription and data management, and they remained skeptical of its ability to perform complex interpretative work. Finally, ethical and sustainability concerns were raised, including algorithmic bias, data privacy, and the environmental impact of AI technologies. The findings reveal persistent epistemological tensions but also highlight emerging opportunities for AI to enhance research efficiency and accessibility, provided that human interpretative agency remains central. Participants stressed the importance of developing robust ethical frameworks, fostering critical reflexivity, and adopting innovative conceptual approaches to responsibly integrate AI into qualitative research and education. This study offers valuable insights for scholars and practitioners navigating the evolving landscape of AI in qualitative inquiry, advocating a balanced approach that leverages AI's potential while safeguarding the human core of qualitative research.