AI and algorithmic literacy among nurses: a concept analysis

To clarify the concept of AI and algorithmic literacy among nurses and to provide a conceptual foundation for nursing education, clinical practice, and responsible AI governance. Rodgers’ evolutionary concept analysis. Guided by Rodgers’ evolutionary method, the literature was analyzed to determine how AI and algorithmic literacy among nurses has been used and conceptualized. Defining attributes, antecedents, consequences, and related concepts were extracted, compared, and synthesized. A systematic search was conducted in Web of Science, PubMed, Embase, and CINAHL. Search terms focused on nurses, nursing students, health workers, artificial intelligence literacy, algorithmic literacy, AI competence, AI readiness, and generative AI literacy. Articles published between January 2020 and June 2026 were screened. Twenty-eight articles were included in the final concept analysis. Four defining attributes were identified: conceptual understanding of AI-mediated nursing contexts; critical interpretation and risk recognition of algorithmic outputs; clinical integration and human oversight of AI recommendations; and ethical governance awareness grounded in professional accountability. Antecedents included AI education and training, digital or informatics foundations, prior AI exposure, individual readiness, organizational support, faculty preparedness, and governance environments. Consequences included improved learning outcomes, critical thinking, AI adoption and readiness, patient safety awareness, human-AI collaboration, and professional innovation. Related concepts included AI literacy, algorithmic literacy, digital literacy, nursing informatics competence, AI readiness, AI competence, and AI self-efficacy. Based on this synthesis, both a brief definition and a full conceptual definition of AI and algorithmic literacy among nurses were proposed. AI and algorithmic literacy among nurses is a multidimensional concept that extends beyond technical knowledge or willingness to use AI. It reflects nurses’ ability to understand, interpret, supervise, and responsibly integrate AI outputs into nursing judgment while maintaining patient safety and professional accountability. Clarifying this concept can support the development of nursing AI education, competency frameworks, measurement tools, clinical training, and governance strategies. As AI becomes increasingly embedded in nursing practice, nurses should be positioned not merely as end users of AI systems but as professional actors responsible for interpreting algorithmic outputs and safeguarding patient care.