Use of Generative Artificial Intelligence in Nuclear Medicine Research, Education, and Clinical Practice: Results from a 2025 Society-Wide Survey.

PURPOSE: Generative artificial intelligence (AI) is rapidly expanding within medical practice, yet its use among nuclear medicine professionals has not been systematically evaluated. This study provides the first society-wide assessment of generative AI adoption among members of the Korean Society of Nuclear Medicine (KSNM). METHODS: An anonymous online survey was distributed to approximately 670 KSNM members. The questionnaire assessed AI use in two domains (research/education and clinical practice), including platforms, frequency, purposes, and perceived usefulness and trust. Descriptive statistics and chi-square tests were used. RESULTS: A total of 122 members responded (estimated response rate, 18.2%); 105 (86.1% of respondents) reported using generative AI. Among users, 51.4% used AI daily and 51.4% used paid services; paid subscriptions were more frequent among daily than non-daily users (58.9% vs. 34.4%, p = 0.021). ChatGPT was the most commonly used platform (89.5%), followed by Gemini (55.2%) and Perplexity (26.7%). Perceived usefulness was higher in research/education (n = 96) than in clinical practice (n = 60): 85.4% vs. 41.7% rated AI as helpful/very helpful (p < 0.001). In research/education, translation/language editing showed high prevalence and high utility, whereas code generation had lower prevalence but high perceived utility. CONCLUSION: Generative AI showed a high adoption rate among the survey respondents, with higher perceived usefulness in research/education than in clinical practice. Given the widespread real-world use of third-party generative AI tools, our findings underscore the need for institutional guidance and privacy-aware governance to ensure safe clinical adoption. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13139-026-01029-0.