Adoption of AI in nursing education- A systematic review of factors influencing student intentions.

AIM: This study seeks to perform a systematic review of the literature on the factors influencing intention to use artificial intelligence (AI) applications among nursing students. This area of research has been increasingly investigated in recent years. BACKGROUND: The continuous evolution of AI poses significant challenges to its acceptance and integration within nursing education. Nurse educators must understand the factors influencing AI adoption to effectively adapt curricula that align with students' needs. DESIGN: Systematic review. METHODS: A systematic search was conducted on Web of Science, Scopus, and PubMed for the previous five years (2019-2025), and 13 studies were identified using PRISMA guidelines. RESULTS: The results revealed several key conclusions: (a) the unified theory and use of technology and the technology acceptance model are the most widely used models; (b) technological, psychological, social, behavioral, and environmental factors can significantly influence intention to use AI among nursing students; and (c) the most frequently identified significant factors were performance expectancy, hedonic motivation, self-efficacy, positive attitudes toward AI, AI anxiety, perception of AI, and facilitating conditions. CONCLUSION: AI-driven instruction encompassing the identified factors is crucial for raising nursing students' willingness to adopt and implement AI in their learning processes. This review goes beyond cataloguing awareness to understanding the drivers of adoption behavior. Hence, nurse educators play a pivotal role in leveraging these factors to design and deliver AI-driven instruction that fosters nursing students' readiness and willingness to adopt emerging technologies in their learning journeys.