Qualitative Research with Artificial Intelligence offers a comprehensive, accessible, and pedagogically rich guide to conducting qualitative research in an era shaped by generative AI, automated analysis, and human–AI collaboration. The book argues that AI can extend analytic visibility, but interpretation, ethics, representation, and responsibility must remain human-led.
The text introduces students and researchers to the philosophical, ethical, methodological, and pedagogical foundations of AI-assisted qualitative inquiry. It covers research design, data collection, transcription, coding, natural language processing, human–AI co-coding, interpretation, reflexivity, trustworthiness, audit trails, writing, and future methodological directions. Throughout, practical boxes, toolkits, reflection prompts, real-world researcher examples, and companion workbook activities help readers translate concepts into accountable research practice. The book emphasizes transparency, data provenance, algorithmic bias, participant protection, and methodological fit, showing how AI can be used critically without reducing qualitative inquiry to automation.
This book is designed for graduate and doctoral qualitative research methods courses, dissertation seminars, research design courses, and scholars seeking practical guidance for ethically integrating AI into qualitative inquiry.