Uso da Inteligência Artificial como ferramenta educacional no ensino de Enfermagem:

Abstract

Introduction: Artificial Intelligence (AI), a term coined by John McCarthy in 1956, has evolved from a theoretical concept into a transformative force across multiple fields, particularly in health and education. Its rapid growth has significantly impacted higher education, fostering a true “silent revolution” in professional training and teaching practice. In nursing, AI emerges as a powerful tool to enhance care delivery, diagnostic accuracy, and educational processes, while preserving the ethical and human roles of nurses. The integration of this technology into academic settings offers opportunities for personalized learning and process optimization but also raises ethical, privacy, and professional adaptation challenges. Objective: To map the scientific knowledge regarding the use of Artificial Intelligence in nursing education. Method: A scoping review was conducted following the Reviewer’s Manual for Scoping Reviews proposed by JBI, using the PCC (Population, Concept and Context) strategy to construct the research question. The search was carried out in the databases National Library of Medicine (PubMed), CAPES Journals, and Latin American and Caribbean Literature in Health Sciences (LILACS) through the Virtual Health Library (VHL). For each item in the search strategy, descriptors and/or synonyms found in the Health Sciences Descriptors and Medical Subject Headings platforms were used: Artificial Intelligence and Education and Nursing. Results and Discussion: The article selection process began with 1,866 imported publications. After applying inclusion criteria, 66 articles were fully analyzed, and 19 were included in the final sample. Most studies adopted qualitative or quantitative approaches, with a predominance of research from the Middle East and Asia. A significant increase in publications was observed in 2025, representing 63.1% of the sample. Thematic analysis identified six main categories, with the most frequent being students’ and educators’ perceptions of AI adoption and studies on curricular frameworks. Only one article addressed ethical, integrity, and governance issues in a structured manner. Conclusions: Despite AI’s potential to enhance education and clinical practice, ethical and structural challenges remain, such as data protection and limited digital preparedness. Its adoption should occur critically and ethically, ensuring the preservation of care quality and humanization.