| Sumario: | This article examines the emerging role of generative artificial intelligence (GenAI), particularly large language models like GPT-4, in assisting qualitative nursing research, which traditionally involves labor-intensive tasks such as coding transcripts, developing themes, and synthesizing findings. Empirical studies indicate that GenAI can significantly accelerate initial coding, theme development, and summarization with substantial overlap to human analysis, though limitations remain—especially in accurate quote attribution, cultural and emotional nuance, and domain-specific precision—necessitating mandatory human oversight and verification. The authors propose a transparent framework for AI-assisted qualitative analysis that restricts AI roles to auditable, reversible, and verifiable tasks while reserving final interpretive authority exclusively for human researchers. They emphasize the need for standardized reporting of AI use in qualitative studies and call for further validation research within nursing contexts, highlighting that responsible AI integration may expand the scale and inclusivity of qualitative nursing research without replacing human judgment.
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