Bridging the Gap Between Potential and Practice

BACKGROUND: Generative artificial intelligence (GAI) has emerged as a transformative tool in health care, particularly with the integration of large language models (LLMs) into electronic health record (EHR) systems. These tools have the potential to enhance clinical decision-making, increase efficiencies, and decrease time in the EHR. However, despite expanding availability, adoption in nursing practice remains limited. This integrative review aimed to synthesize the literature and explore barriers related to the integration of GAI tools into nursing practice. METHODS: We conducted an integrative search of peer-reviewed literature published between November 2022 and July 2025 to examine the current evidence while assessing for methodological quality. The retrieved articles were screened for title, abstract, and full text eligibility. We synthesized themes related to GAI adoption by nurses, focusing on ethical, educational, and workflow-related factors that influence use. RESULTS: A total of 10 studies met criteria including 7 qualitative descriptive design, 2 case reports, and 1 experimental clinical trial. Four key barriers emerged: educational gaps, ethical concerns, data transparency issues, and workflow misalignment contributing to nurses' hesitancy to engage with GAI tools. Recommendations include involvement of nurses in the design, implementation, and evaluation of GAI tools and mandatory AI curricula in nursing education. CONCLUSIONS: Overcoming barriers requires nurse involvement in GAI design efforts, targeted education, and governance models that foster trust and usability. Nurse-centered integration of GAI tools has the potential to advance workforce efficiencies while preserving patient safety.