Generative AI in Nursing Education: Nurse Educators' Perceptions of Readiness, Trust, and Clinical Judgment

Abstract

Higher education, including nursing education, is increasingly visible when using generative artificial intelligence (GenAI) in teaching. These tools open new opportunities but also raise critical questions about clinical reasoning, professional judgment, and patient safety. This study explores nurse educators' experiences using GenAI in nursing education, including their readiness to adapt teaching practices and professional roles, their perceptions of opportunities and challenges, and the required competencies and institutional support. This study used a qualitative exploratory descriptive research design. Maximum variation purposive sampling was used to select seven nurse educators with more than two years of teaching experience and prior exposure to GenAI. We conducted semi-structured individual interviews via Zoom and analyzed the data using thematic analysis. Nurse educators’ readiness to integrate GenAI varied greatly and was influenced more by professional trust than by ability to use GenAI. Accuracy of GenAI-generated content was a critical factor in developing trust and needed verification. The threat of students losing their clinical judgment when using AI was a major concern for all participants. They felt that GenAI should be used in a ‘supportive’ manner, while hands-on teaching and direct interaction between the educator and student remained central to learning. Participants felt that they lacked formal training in GenAI and instead learned through self-directed learning and guidance from peers. Many wanted more guidance from their institutions, but differed on the level of support or restrictions needed for safe integration. The findings indicate that integration of GenAI into nursing education requires more than training in the use of the technology.