Last semester, a student asked me whether it was acceptable to use an artificial intelligence (AI) platform to summarize a complex clinical guideline. The question sparked an important discussion. The issue was not whether the student could access information using AI, but whether they could evaluate the accuracy of that information and apply it appropriately to patient care. As we discussed the strengths and limitations of AI-generated content, it became clear that today’s nurse must develop the skills to critically evaluate AI outputs while maintaining accountability for patient care. As AI becomes increasingly integrated into healthcare, AI literacy is emerging as an essential nursing competency.
Artificial intelligence is rapidly transforming healthcare, and nursing is no exception. From clinical decision-support systems to ambient documentation tools that generate clinical notes, AI is becoming integrated into healthcare delivery. As healthcare organizations explore AI-enabled technologies, nurses will be called upon to evaluate their impact on patient care, safety, and professional practice.
Nurses already encounter AI in their workplaces, often without realizing it. Electronic health records use predictive algorithms to identify patients at risk for deterioration, falls, or readmission. AI-powered documentation tools can summarize patient encounters and assist with charting. Recent studies have demonstrated that AI-assisted documentation can reduce administrative burden, improve efficiency, and decrease clinician burnout, allowing providers to spend more time focused on patient care (Duggan et al., 2025).
While AI offers significant opportunities, it is not without limitations. AI systems may generate inaccurate information, perpetuate bias, or fail to recognize important clinical nuances. For this reason, AI should never replace professional nursing judgment. Rather, it should be viewed as a tool that supports clinical decision-making while preserving the nurse’s responsibility for patient assessment, interpretation of data, and clinical reasoning. Nurses remain accountable for evaluating and validating AI-generated information before incorporating it into practice (El-Banna et al., 2025).
The growing presence of AI in healthcare highlights the need for AI literacy among nurses. AI literacy extends beyond learning how to use technology; it includes understanding the capabilities and limitations of AI, recognizing ethical concerns, protecting patient privacy, and critically evaluating AI-generated recommendations (El-Banna et al., 2025).
Nursing education also plays a critical role in preparing future nurses for an AI-enhanced healthcare environment. Rather than focusing solely on preventing students from using AI tools, educators should help students learn to use them responsibly. Emerging evidence suggests that AI-assisted learning can enhance student engagement and readiness for practice when paired with reflective learning and critical thinking activities (Cucci et al., 2025).
Whether practicing at the bedside, in primary care, administration, or academia, nurses have an opportunity to shape how AI is integrated into healthcare. By embracing lifelong learning and maintaining a commitment to critical thinking and patient advocacy, the nursing profession can help ensure that AI serves as a tool to enhance, not replace the human connection at the heart of nursing.
Disclosure: The author used generative AI to enhance the clarity and structure of the article. After using the tool, the author reviewed and edited the work as needed and takes full responsibility for the content of this publication.
References
Cucci, F., Marasciulo, D., Romani, M., Soldano, G., Cascio, D., De Nunzio, G., & Conte, L. (2025). The contribution of artificial intelligence in nursing education: A scoping review of literature. Nursing Reports, 15, 283. 10.3390/nursrep15080283
Duggan, M. J., Gervase, J., Schoenbaum, A., Hanson, W., Howell, J. T., Sheinberg, M., & Johnson, K. B. (2025). Clinician experiences with ambient scribe technology to assist with documentation burden and efficiency. JAMA Network Open, 8(2), e2460637. 10.1001/jamanetworkopen.2024.60637
El-Banna, M. M., Sajid, M. R., Rizvi, M. R., Sami, W., & McNelis, A. (2025). AI literacy and competency in nursing education: Preparing students and faculty members for an AI-enabled future—A systematic review and meta-analysis. Frontiers in Medicine, 12 https://doi.org/10.3389/fmed.2025.1681784
