Type: article
Abstract: Qualitative interviewing is a cornerstone of information systems (IS) research, yet it remains resource-intensive, difficult to scale, and constrained by interviewer-related variability. Recent advances in conversational artificial intelligence (AI) make it possible, for the first time, for the interviewer to be non-human, opening methodological opportunities while challenging the relational, interpretive, and reflexive facets of qualitative inquiry. Despite the growing availability of AI-led interviewing tools, methodological guidance for their rigorous integration into IS research is largely absent. Drawing on a systematic literature review, sixteen AI-led interviews on conspiracy beliefs, and sixteen subsequent human-led reflection interviews, we develop a framework that includes key insights and practical advice for conducting rigorous AI-led interviews. We find that methodological rigor shifts from interpersonal performance toward design rigor, and that the researcher’s positionality is relocated upstream into prompts, interface, and system architecture, calling for an expanded standard of methodological transparency in qualitative IS research.
Institution: University of Göttingen
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7222990422