Background: Safe medication administration is a fundamental aspect of nursing practice and a core component of patient safety. However, systemic failures, workload pressures, and educational gaps continue to contribute to medication errors, posing persistent challenges for healthcare systems. In this context, innovative educational technologies, particularly Artificial Intelligence (AI), have emerged as promising strategies to support the development of competencies related to safe medication administration. Methods: This scoping review aimed to map evidence on AI-based tools used to teach safe medication administration in nursing. The review was conducted in accordance with the Joanna Briggs Institute (JBI) methodology and reported following the PRISMA-ScR guidelines. Searches were performed in PubMed, Scopus, Web of Science, LILACS, and Google Scholar, covering studies published between 2010 and October 2025 in English, Portuguese, and Spanish. Study selection was conducted in two stages, followed by standardized data extraction. Results: A total of 545 records were identified, of which only two studies met the eligibility criteria. The included studies, conducted in Israel and South Korea, evaluated a microlearning chatbot and Large Language Model (LLM)-based tools designed to support teaching safe medication administration. Both studies demonstrated improvements in knowledge and performance in tasks and simulations related to the medication process, as well as positive acceptability among participants. However, neither study assessed direct clinical outcomes, such as reductions in medication errors or preventable adverse events. Conclusions: Although AI-based educational tools show potential to enhance competencies related to medication safety in nursing, the available evidence remains limited. Further robust, multicenter, and comparative studies are needed to evaluate their impact on clinical outcomes and to support their integration into nursing education and practice.
Oliveira et al. (Tue,) studied this question.