Undergraduate nursing students' attitudes and needs regarding the use of generative artificial intelligence in professional learning: a qualitative study

Objective This study aimed to explore undergraduate nursing students ‘attitudes toward and needs regarding the use of generative artificial intelligence (AI) in professional learning, to provide a reference for the better integration of generative AI into nursing education. Methods This study employed a qualitative research design. Guided by Colaizzi's seven-step method, semi-structured in-depth interviews were conducted with 18 undergraduate nursing students with experience in using generative AI. Participants were recruited through purposive sampling from three universities in China between January and March 2026. Results Two themes and six subthemes were identified: (1) undergraduate nursing students have a rational attitude toward generative AI, including broadening learning perspectives and improving learning efficiency, alleviating psychological anxiety, and existing concerns; (2) undergraduate nursing students ‘needs regarding the use of generative AI in professional learning, including information accuracy, humanistic care, and external support. Conclusion Undergraduate nursing students generally adopt a rational and accepting attitude toward generative AI. While recognizing its value as a learning aid, they maintain a clear understanding of its limitations and have expressed a pressing need for accurate information, humanistic care, and external support. Nursing institutions should strengthen the regulation, guidance, and integration of generative AI into teaching to promote the high-quality training of nursing professionals.