As we step into a new year, I find myself returning to the same conversations again and again, with faculty colleagues, clinical partners, students, and even friends outside of nursing. How do we implement artificial intelligence (AI) ethically and responsibly in our school? How do we increase AI literacy without overwhelming an already stretched workforce? And how do we ensure that no one feels left behind as the technology continues to accelerate? These questions are no longer abstract. They are shaping curriculum discussions, faculty meetings, and informal hallway conversations as nurse educators and leaders try to navigate rapid technological change while staying grounded in nursing’s values.
Emerging evidence suggests that this tension reflects real gaps in preparedness rather than resistance. Student nurses, for example, appear broadly optimistic about AI. Labrague et al. (2023) found that student nurses reported favorable perceptions of AI utilization in nursing practice, expressed high intentions to adopt AI technologies, and held generally positive attitudes toward their future use. In contrast, practicing nurses often report limited awareness of AI’s scope and impact in healthcare, even as AI-enabled tools become increasingly embedded in clinical systems (Alruwaili et al., 2024). Together, these findings reveal a profession that is open to innovation, but unevenly equipped to engage with it confidently and safely.
In nursing education, this gap is particularly visible. Ehmke et al. (2025) identified significant knowledge and skill gaps among nursing faculty related to generative AI, despite generally neutral to positive attitudes. Importantly, their findings emphasize the role of institutional support like hands-on training, mentorship, and clear policies, as essential for enhancing AI literacy among faculty and enabling them to integrate AI responsibly into teaching and assessment. Without these supports, the pace of student readiness may outstrip educators’ capacity to guide ethical and effective use.
Hoelscher et al. (2025) argue that AI literacy should be understood as a core professional competency rather than a niche informatics skill. Their N.U.R.S.E.S. framework positions nurses and educators as active participants who can critically evaluate AI tools, understand their limitations, and apply them ethically in both learning and practice environments. This framing aligns well with students’ positive attitudes toward AI (Labrague et al., 2023), but it also highlights a critical bottleneck: faculty preparedness.
In clinical practice, AI is already influencing how nursing work is organized and experienced. Yakusheva et al. (2025) describe how AI technologies may redistribute cognitive and documentation tasks, potentially freeing nurses’ time for direct patient care, education, and coordination. When implemented thoughtfully, AI can support clinical decision-making and reduce low-value administrative burden. However, the authors caution that these benefits are not automatic. If efficiency gains are used primarily to justify increased workloads without corresponding workflow redesign or staffing support, AI risks intensifying strain rather than alleviating it (Yakusheva et al., 2025). The impact of AI on nursing practice, therefore, depends less on the technology itself and more on leadership choices surrounding implementation.
Ethical use of AI must remain central across both education and practice. Hoelscher et al. (2025) emphasize that AI does not replace professional accountability; nurses remain responsible for verifying outputs, recognizing bias, and ensuring patient safety. Alruwaili et al. (2024) further explain that limited awareness of AI’s capabilities and risks can undermine safe and effective use. Ethical nursing practice requires more than basic familiarity with AI tools; it demands critical understanding, transparency in documentation, and vigilance to ensure that AI does not exacerbate inequities or obscure clinical judgment.
Ultimately, the throughline across these studies is leadership. In conversations with faculty and colleagues, what emerges most clearly is not fear of AI itself, but uncertainty about expectations, boundaries, and support. The evidence reinforces this lived experience: students are eager, nurses are cautiously open, and faculty are asking for guidance rather than mandates (Alruwaili et al., 2024; Ehmke et al., 2025; Labrague et al., 2023). Nurse leaders and educators are uniquely positioned to respond by normalizing AI literacy, investing in hands-on training and mentorship, and establishing clear institutional policies that make responsible use the default rather than the exception.
AI should not be framed as a replacement for nursing or a threat to professional identity. It should be understood as an assistant: one that can enhance education, support safer care, and improve patient outcomes when guided by human expertise and ethical intent. If we lead with curiosity, transparency, and compassion, we can move the profession forward together, ensuring that technological progress strengthens nursing rather than leaving anyone behind.
References
Alruwaili, M. M., Abuadas, F. H., Alsadi, M., Alruwaili, A. N., Elsayed Ramadan, O. M., Shaban, M., … El Arab, R. A. (2024). Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice. Digital Health, 10, 20552076241271803. https://doi.org/10.1177/20552076241271803
Ehmke, S. D., Bridges, J., & Patel, S. E. (2025). Self-perceived knowledge, skills, and attitude of nursing faculty on generative artificial intelligence in nursing education: A descriptive, cross-sectional study. Teaching and Learning in Nursing. (20) (222-227) https://doi.org/10.1016/j.teln.2025.01.029
Hoelscher, S. H. (2025). N.U.R.S.E.S. embracing artificial intelligence: A guide to artificial intelligence literacy for the nursing profession. Nursing Outlook. 73 (4) https://doi.org/10.1016/j.outlook.2025.102466
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., Sabio, J. B., & de Los Santos, J. A. (2023). Student nurses’ attitudes, perceived utilization, and intention to adopt artificial intelligence (AI) technology in nursing practice: A cross-sectional study. Nurse Education in Practice, 73, 103815. https://doi.org/10.1016/j.nepr.2023.103815
Yakusheva, O., Bouvier, M. J., & Hagopian, C. O. P. (2025). How artificial intelligence is altering the nursing workforce. Nursing Outlook, 73(1). https://www.nursingoutlook.org/article/S0029-6554(24)00193-3/fulltext
