Artificial intelligence (AI) is increasingly integrated into nursing education and healthcare, emphasizing its significance, applications, benefits, and challenges. AI in nursing curricula focuses on equipping students with essential skills to deliver safe and effective patient care in a rapidly evolving healthcare environment. Applications include AI-driven clinical decision support systems, simulations, virtual patients, and exploration of AI ethics. These tools enhance critical thinking, decision-making, and data analysis in healthcare contexts.This review summarizes AI's role in clinical practice, covering disease diagnosis, treatment planning, patient engagement, and ethical considerations while highlighting the need for human expertise in AI adoption.: 1. To enhances understanding of AI’s significance in Nursing Education; 2. To explore the impact of applying AI in nursing Education. 3. To promote AI usage in Nursing Institutions.This review analyzed AI's integration into healthcare and nursing education using indexed literature from PubMed, Scopus, and EMBASE. Key issues include data privacy, algorithm transparency, and biases, requiring responsible AI implementation. Effective strategies include curriculum design, faculty training, hands-on practice, industry collaboration, and continuous learning. Research highlights AI's role in improving diagnosis, treatment planning, personalized medicine, mental health support, and patient education while enhancing accuracy, reducing costs, and minimizing errors. Scholars have explored virtual simulations, faculty and student perspectives, AI competencies, and ethical concerns. Academic journals, conferences, and credible online sources provide valuable insights into AI's impact on nursing education and student outcomes.: In conclusion, integrating AI into nursing education is a developing field with great potential to enhance learning and prepare nurses for AI-driven healthcare. Research covers topics like virtual simulations, AI competencies, ethical concerns, and stakeholder perspectives. Key resources include academic journals, conferences, and online databases.AI supports disease diagnosis, personalized treatment, and clinical decision-making, aiming to improve patient care rather than just automating tasks. However, challenges like data privacy, bias, and the need for human expertise must be addressed.By tackling these challenges and promoting responsible AI use, nurse educators can equip future nurses with the skills needed for the evolving healthcare landscape.
Read full abstract