[Sustainable Development and the Challenges of Integrating AI Into Evidence-Based Practice]

Under the framework of evidence-based practice (EBP), evidence-based knowledge is integrated systematically into clinical care and continuously updated to enhance decision-making, ensure patient safety, and showcase nursing excellence. The rapid evolution and popularization of artificial intelligence (AI) has encouraged its incorporation into EBP, including as a tool for clinical nurses to further increase efficiencies in care provision and decision-making. However, AI integration poses challenges in terms of both care practices and ethics. This article was designed to explore the various applications of AI in EBP, emphasizing sustainability alongside ethical, institutional, and technological issues. While AI can improve care efficiency and quality, it also introduces risks such as data errors, algorithmic bias, privacy concerns, intellectual property issues, access inequities, and ethical accountability concerns. Without transparency and oversight, large language models have the potential to exacerbate health disparities and resource gaps. To achieve the core values of improving care quality and patient safety through technology, integrating AI into EBP requires the building of a robust framework that is clinically practical, regularly updated with new algorithms, and includes monitoring systems and ethical governance. Ultimately, the harmonization of AI capabilities and care principles may be expected to achieve healthcare that is more resilient, value-driven, high-quality, and sustainable.