Abstract
[This is an excerpt.] Generative AI (GenAI) technologies like ChatGPT have rapidly transformed healthcare, offering unprecedented capabilities in natural language processing, image generation, and complex data analysis (Choudhury and Shamszare 2023; Hobensack et al. 2024; Singh et al. 2023). In nursing, these advancements promise revolutionary benefits: voice recognition tools that streamline documentation and free nurses for direct patient care (Joseph et al. 2020), automated systems that reduce administrative burden, and analytics platforms that provide real-time decision support while reducing information overload (Choudhury and Chaudhry 2024; Choudhury and Shamszare 2023). However, while literature extensively documents these potential benefits, it inadequately addresses the significant risks GenAI poses to nursing practice. The enthusiastic promotion of these technologies often overshadows critical discussions about patient safety and care quality concerns (Bragazzi and Garbarino 2024; Park et al. 2024). These underexamined risks include ethical dilemmas in decision-making autonomy, data privacy vulnerabilities, and “hallucinations”—fabricated information that could compromise patient outcomes (Bragazzi and Garbarino 2024; Park et al. 2024). Furthermore, GenAI may exacerbate healthcare disparities when underlying training data fails to represent diverse demographic, cultural, and socioeconomic characteristics (Hostetler et al. 2024). This editorial addresses this imbalance by highlighting these overlooked risks and advocating for informed GenAI integration in nursing practice, drawing insights from an International Think Tank workshop held in November 2024 at the Brocher Foundation, where the Nursing AI Leadership Collaborative (NAIL https://www.nailcollab.org/) convened 20 experts from diverse fields to develop recommendations for embedding nursing expertise in AI health technologies. [To read more, click View Resource.]
