Artificial Intelligence (AI) has rapidly advanced and is increasingly integrated into medical education to improve teaching quality and learning outcomes. This study explored the impact of AI-assisted teaching on nursing interns’ learning effectiveness and satisfaction during clinical practicum. A cross-sectional survey was conducted, with 120 questionnaires distributed and 98 valid responses collected. The survey examined convenience of AI-assisted learning, its influence on clinical judgment accuracy, and perceptions of AI’s role in interaction and communication. Results indicated that 76% of respondents reported enhanced learning efficiency, particularly in clinical decision-making and case analysis, due to AI’s real-time feedback. Furthermore, 82% expressed satisfaction with AI-based teaching methods, emphasizing personalized support and structured guidance in complex nursing skill training. Several interns highlighted that AI promoted self-directed learning by tailoring content to individual needs. However, 28% noted concerns that reliance on AI might reduce interpersonal communication, potentially limiting emotional engagement and collaboration with patients and healthcare professionals. Overall, findings suggest AI can significantly improve nursing education by enhancing both learning outcomes and satisfaction. Future efforts should focus on optimizing AI platforms and conducting long-term evaluations, while ensuring a balance between technological support and interpersonal interaction to maintain the holistic nature of nursing education.

I have nearly eight years of clinical experience. My research focuses on cancer care, including breast cancer treatment and supportive care. With the rapid development AI globally, I am currently dedicated to researching its applications in healthcare and nursing information, aiming to improve information integration and management in future care.