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Generative Artificial Intelligence (AI) technology landed on the scene in the late 1950s and continues to rapidly evolve (Salesforce, n.d.). Generative AI offers a range of applications to the field of nursing. Generative AI is impactful in patient care and providing nursing training. From nursing experience, simulation training provides realistic experiences in patient scenarios to enhance experience and build skills. A randomized control study on nursing students compared virtual reality simulation training for sepsis with an AI-powered provider versus a human-controlled (Leung et al., 2023). The virtual reality simulation was in place to address concerns about communication between nurses and providers during sepsis scenarios (Leung et al., 2023). The study found that AI-powered doctors were non-inferior to human-controlled virtual reality simulations (Leung et al., 2023). The articles offer that nursing training and simulation can be beneficial through AI technology.
Beyond nursing practice, generative AI technology is considerably influential in prompting a consumer empowerment trend in the current Knowledge era (McGonigle & Mastrian, 2025). AI technology significantly enhances patient education and empowers the patient. The study by Marey et al. (2023) suggests that in patients with cardiovascular disease, generative AI offers tailored educational material to patients through generative AI models like natural language processing and vision-based models. The utilization of generative AI, especially as generative AI evolves, can tailor patient educational materials to the patient’s level and learning needs.
Though the power and future of generative AI in nursing and patient education are mighty, some factors of the technology make it unique. Generative AI is intriguing in many ways, but one of the most intriguing aspects is that on a different day, the same question can produce different results. The unpredictability of generative AI is classified as randomness (Ugander & Epstein, 2024). The article by Ugander and Epstein (2024) stresses that AI in creative contexts depends on efficiency and human randomness.
Generative AI in nursing, patient education, and the randomness of AI are important in various ways and impact the nurse administrator role. As Leung et al. (2023) stated, generative AI offers healthcare staff training and development. Generative AI in providing more tailored patient education can improve patient engagement in care and patient satisfaction. Nurse administrators can apply generative AI to assess the quality of care for specific metrics like patient-sustained falls or central line-associated bloodstream infections. In identifying these metrics, nurse administrators can again utilize generative AI to provide staff with more directed education and training.
References
Leung, T., Yamane, S., Brown, M., Liaw, S.Y., Tan, J.Z., Bin Rusli, K.D., Ratan, R., Zhou, W., Lim, S., Lau, T.C., Seah, B., & Chua, W.L. (2023, July 26). Artificial Intelligence versus human-controlled doctor in virtual reality simulation for sepsis team training: Randomized controlled study. Journal of Medical Internet Research, 25. https://doi.org/10.2196/47748Links to an external site.
Marey, A., Saad, A. M., Killeen, B. D., Gomez, C., Tregubova, M., Unberath, M., & Umair, M. (2023). Generative Artificial Intelligence: Enhancing patient education in cardiovascular imaging. BJR|Open, 6(1). https://doi.org/10.1093/bjro/tzae018
McGonigle, D. & Mastrian, K. G. (2025). Nursing informatics and the foundation of knowledge. (6th Ed.). Jones & Bartlett Learning.
Salesforce. (n.d.). What is the history of Artificial Intelligence (AI)?. Tableau. https://www.tableau.com/data-insights/ai/history#:~:text=Birth%20of%20AI%3A%201950%2D1956&text=The%20term%20%E2%80%9Cartificial%20intelligence%E2%80%9D%20was,intelligence%20called%20The%20Imitation%20Game.
Ugander, J., & Epstein, Z. (2024). The art of randomness: Sampling and chance in the age of algorithmic reproduction. Harvard Data Science Review, 6(4). https://doi.org/10.1162/99608f92.f5dcab1a
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