AI literacy and generative AI acceptance among surgical and operating room nurses in Türkiye: a cross-sectional study with an open-ended qualitative component

The integration of artificial intelligence (AI) in surgical environments requires high digital competencies and technology acceptance among perioperative nurses. This study aimed to determine the AI literacy and generative AI acceptance levels of surgical and operating room nurses, and to examine the associated factors. A cross-sectional study with an open-ended qualitative component was conducted. A convenience sample of 305 nurses who were members of the Turkish Surgical and Operating Room Nurses Association was recruited between March and June 2026. Data were collected using a sociodemographic and AI usage characteristics form, the AI Literacy Scale, and the Generative AI Acceptance Scale. Quantitative data were analyzed using descriptive statistics, independent samples t-tests, ANOVA, Pearson correlation, and multiple linear regression. Responses to the open-ended question were analyzed thematically. The mean AI literacy and generative AI acceptance scores were 46.66 ± 7.04 and 79.16 ± 13.91, respectively. AI literacy was moderately correlated with acceptance ( r = 0.498, p < 0.001). The regression model explained 40.6% of the variance in generative AI acceptance (R²=0.406, p < 0.001). Overall AI literacy (β = 0.376), perceived workload reduction (β = 0.291), professional AI use (β = 0.171), and basic AI knowledge (β = 0.132) were significant predictors. Patient safety was the top-priority education topic. Among the 76 participants who answered the open-ended question, thematic analysis identified three themes: practical and technical AI competencies; information security, data privacy, and ethical responsibilities; and psychosocial support. Higher AI literacy, active professional use, knowledge of AI applications, and the expectation of workload reduction were associated with greater acceptance of generative AI among participating perioperative nurses. Patient safety was the top education priority, and responses from the 76 participants who answered the open-ended question highlighted additional needs for practical AI skills, information security, data privacy, ethical responsibilities, and psychosocial support. Safe AI integration in perioperative care will require practice-based education supported by robust patient-safety, ethical, and data-governance safeguards.