Exploring the Ethical Landscape of Artificial Intelligence in Nursing Practice: A Bibliometric Analysis

Background: The integration of Artificial Intelligence (AI) into nursing practice is rapidly advancing, offering potential improvements in clinical accuracy, decision-making, and service efficiency. However, this acceleration also introduces ethical challenges related to data privacy, algorithmic transparency, accountability, and fairness in healthcare delivery. Objective: This study aims to map the scientific landscape of ethical issues surrounding the use of AI in nursing practice through a bibliometric approach. Methods: Data were retrieved from the Web of Science Core Collection on October 30, 2025, using keywords related to AI, ethics, and nursing. The inclusion criteria comprised English-language research articles and reviews published between 2019 and 2025. A total of 68 articles met the eligibility criteria and were analyzed using the Web of Science Analysis Tools, VOSviewer (v.1.6.20), and Microsoft Excel to map publication trends, author and institutional collaborations, and thematic structures based on co-authorship, bibliographic coupling, and keyword co-occurrence. Results: Publications increased sharply from one article in 2019 to 35 in 2025, indicating growing global attention to the ethical dimensions of AI in nursing. The United States, China, and the United Kingdom emerged as the leading contributors, with international researcher collaborations forming three distinct clusters. BMJ Open , Nursing Ethics , and BMC Nursing were identified as the most influential journals. The dominant keywords included artificial intelligence , nursing ethics , machine learning , decision-making , and AI literacy , forming four thematic clusters: ethics and data, generative AI and decision-making, robotics in care, and digital literacy. The most cited articles highlighted the opportunities and challenges of generative AI in clinical practice and education. Conclusion: The application of AI in nursing is rapidly expanding but is accompanied by significant ethical dilemmas. The bibliometric analysis revealed a global focus on privacy, accountability, algorithmic fairness, and nursing preparedness. Strengthening AI literacy, establishing ethical governance frameworks, and developing adaptive policies are essential to ensure the responsible and patient-centered implementation of AI technologies.