Attitudes toward artificial intelligence in nursing education, research, and clinical practice: a cross-sectional survey of Iranian faculty, nurses, and students

BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare, offering opportunities to enhance accuracy, efficiency, and personalized care in nursing. However, successful integration depends on the attitudes and readiness of nursing professionals and students. Limited evidence exists on these perspectives in the Iranian context. OBJECTIVE: This study aimed to assess the attitudes of Iranian nursing groups-including faculty members, clinical nurses, and nursing students-toward the functions of artificial intelligence in education, research, and clinical practice. METHODS: A cross-sectional online survey was conducted in Iran in 2025. Data were collected using a researcher-developed, anonymous, 34-item questionnaire assessing attitudes across education, research, and clinical domains on a 5-point Likert scale. The questionnaire was distributed via email and social media networks. Of 300 distributed questionnaires, 161 valid responses were analyzed using descriptive and inferential statistics in SPSS version 25. RESULTS: The mean total attitude score was 123.14 ± 16.38 (item mean 3.62/5), indicating moderate to good overall attitudes. Attitudes were more favorable in education (30.24 ± 4.91) and research (18.88 ± 2.63) than in clinical practice (73.99 ± 10.55). Faculty members (133.39 ± 13.86) and nursing students (127.68 ± 15.15) reported significantly higher scores than clinical nurses (116.25 ± 16.19) (p < 0.001). Female participants showed more positive attitudes than males (p = 0.01). No significant associations were found with age or work experience. CONCLUSION: Iranian nursing groups exhibit generally positive attitudes toward AI, with greater acceptance in educational and research domains compared to clinical applications. Targeted training programs, particularly for clinical nurses, and integration of AI concepts into nursing curricula are recommended to address gaps and promote effective adoption in Iran's healthcare system.