Artificial intelligence (AI)-based technologies are rapidly expanding across healthcare systems and health sciences education, with generative AI increasingly integrated into clinical decision-making, patient monitoring, workflow management, rehabilitation, and postoperative care (1). In this evolving context, professional literacy is a fundamental component of nursing education and practice, enabling nurses to interpret professional documents, appraise scientific evidence, communicate effectively, and apply knowledge across diverse healthcare settings (2). As AI becomes embedded in healthcare delivery, professional literacy is also evolving to encompass human–technology interaction and the ability to understand, critically evaluate, and use AI responsibly. Accordingly, AI literacy should be regarded not as a separate technical skill but as an integral and evolving component of professional nursing literacy. This perspective also supports the view that technology may represent a potential fifth domain of the nursing metaparadigm, alongside person, environment, health, and nursing (3).
However, integrating AI into healthcare presents ethical and technical challenges, including overreliance, erosion of clinical judgment, algorithmic bias, privacy risks, and threats to patient safety. The limited transparency of some advanced systems, particularly “black-box” deep-learning models, underscores the need for explainable AI and governance frameworks that address transparency, accountability, data protection, and continuous monitoring (4). Nurses should therefore move beyond passive adoption by participating in the evaluation, validation, and responsible implementation of AI systems; identifying limitations and errors; assessing outcomes; and contributing to safer healthcare solutions.
Healthcare professionals’ preparedness has not kept pace with the rapid development and adoption of AI. This gap is also evident among Iranian nursing students, who increasingly use and encounter AI tools, whereas their AI knowledge and attitudes remain moderate and their practical application of AI is limited. These findings highlight the need to strengthen AI literacy and preparedness for responsible use (5). Moreover, the integration of AI into nursing education may be constrained by gaps in AI-focused curricula, faculty readiness (6), nursing informatics competencies, and digital infrastructure (7). Thus, the central challenge is not merely access to AI technologies, but also ensuring that nurses possess the knowledge, skills, and professional judgment required to use them safely, ethically, and effectively.
Redefining professional literacy in nursing requires integrating AI literacy training and practical workshops into nursing education and continuing professional development. Simulation- and case-based learning can help nurses practice real-world scenarios, evaluate the accuracy and reliability of AI-generated outputs against scientific evidence and patient-specific conditions, and develop appropriate clinical responses. Prompting skills should also be included to enable nurses to formulate precise, purposeful, and patient-centered queries. Clinical decision-making should follow a human–AI collaboration model in which AI functions as a decision-support tool rather than a substitute for professional judgment. Nurses must retain ultimate responsibility for clinical decisions and care outcomes. Interdisciplinary collaboration among nurses, data specialists, and ethics experts is also essential to designing, evaluating, and implementing nurse-centered AI technologies and to strengthening professional ownership.
Taken together, AI can function as a clinical compass only when it enhances—not replaces—professional judgment. Its safe and ethical use requires human oversight, critical appraisal of outputs, algorithmic transparency, and professional accountability. Without these safeguards, overreliance on algorithmic recommendations may undermine professional autonomy and compromise the quality of care, turning AI into a “digital crutch.”
Therefore, AI literacy should be recognized as a core professional competency alongside effective patient communication, accurate documentation, and clinical reasoning. Updating nursing competency standards and embedding AI-related competencies into nursing curricula and clinical practice are essential to ensure safe, ethical, autonomous, and human-centered care in an AI-enabled healthcare environment.
