Qualitative Research in the Age of Artificial Intelligence

This book examines how generative artificial intelligence is reshaping qualitative research methodology and argues that AI can support qualitative inquiry but cannot replace human judgment, contextual understanding, ethical sensitivity, reflexivity, and interpretive labour. Across six chapters, it moves from diagnosis to construction. It revisits the humanistic foundations of qualitative inquiry, then works through the sites where AI now mediates practice: data generation and transcription; coding and theme development; reflexivity, positionality, and researcher presence; and ethics, trustworthiness, and accountability. Each is grounded in verifiable cases, including documented speech-to-text hallucinations in clinical settings, consent litigation over AI notetakers, regulatory action against major AI providers, and empirical comparisons of AI-generated and human-generated themes. Together, these show that AI reproduces the form of interpretation without its substance, performing descriptive work credibly while failing on latent meaning, silence, contradiction, and cultural nuance. The book culminates in an original contribution, the Human-Centred AI-Assisted Qualitative Research (HC-AIQ) Framework, six interlocking principles operationalised across the research lifecycle and supported by practical protocols, audits, checklists, and disclosure templates. It is written for postgraduate students, early-career researchers, and supervisors, and for ethics committees, journal editors, reviewers, and senior scholars who must set or apply standards for AI use in qualitative scholarship across the social, health, and education sciences.