Artificial intelligence (AI) is constantly improving the quality of medical procedures. Despite the application of AI in the healthcare industry, there are conflicting opinions among professionals, and limited research on its practical application in Saudi Arabia was conducted. Aim: To assess the nurses’ knowledge regarding the application of AI in practice at one of the Ministry of Health hospitals in Saudi Arabia. Methods: Descriptive cross‐sectional research using convenience sampling in January 2023 involving 307 staff nurses, using a single 11‐item questionnaire. In addition, 6 closed‐ended questions were used to assess the knowledge, possible risks, and advantages of AI. Results: All 307 participants completed the survey and used it for data analysis using SPSS V.25. Kruskal–Wallis and Whitney tests and descriptive statistics were used to identify the significant differences among groups. The study results reveal significant differences between age groups and working locations regarding familiarity with AI and future use of AI. In contrast, a considerable difference exists between licensed years groups regarding familiarity with AI. Surprisingly, education level does not affect AI knowledge. Additionally, the future use of AI is significantly affected by the nurse’s gender. Limitation: Nurses were not included in previous studies on AI, and most nursing participants need more interest in AI. Conclusion: The study’s results showed that nurses have positive opinions of AI in the healthcare industry, which will help them speed up procedures and reduce medical errors. AI applications can expand in healthcare by increasing the use of AI in the healthcare industry to improve care quality and encourage academic institutions to develop best practices for deploying AI applications in the healthcare industry.

The integration of artificial intelligence into healthcare is rapidly transforming clinical practice. Nurses' acceptance of artificial intelligence is influenced by their digital literacy and ethical awareness, yet empirical evidence examining these interrelationships is limited. We aimed to examine the direct and indirect effects of digital literacy on nurses' acceptance of artificial intelligence, with ethical awareness of artificial intelligence serving as a mediating factor. A cross-sectional, correlational design was conducted among 350 nurses working in medical-surgical and critical care units at El-Kasr Al-Aini hospital in Egypt from March 2025 to December 2025. Participants completed validated instruments assessing digital literacy, artificial intelligence ethical awareness, and artificial intelligence acceptance. Data were analyzed using descriptive statistics, Pearson correlations, and structural equation modeling (SEM) with bootstrapping to assess mediation effects. Participants demonstrated moderate levels of digital literacy, artificial intelligence ethical awareness, and artificial intelligence acceptance. SEM analysis revealed that digital literacy had a significant direct effect on artificial intelligence acceptance (β = 0.29, p < 0.001) and a strong effect on artificial intelligence ethical awareness (β = 0.46, p < 0.001). Artificial intelligence ethical awareness significantly mediated the relationship between digital literacy and artificial intelligence acceptance (indirect effect β = 0.13, p < 0.001), indicating partial mediation. The model exhibited good fit indices: chi-square/df (χ²/df) = 1.98, Comparative Fit Index= 0.95, Tucker-Lewis Index= 0.93, Root Mean Square Error of Approximation= 0.057, and Standardized Root Mean Square Residual= 0.045. Digital literacy enhanced participants' acceptance of artificial intelligence both directly and indirectly through ethical awareness. Ethical preparedness may, therefore, be a critical factor alongside technical competence in promoting artificial intelligence adoption among Egyptian nurses. Integrating digital literacy training with ethical education in Egyptian nursing curricula and continuing professional development programs may be able to facilitate safe and effective artificial intelligence adoption, supporting high-quality patient care in technologically advanced healthcare environments.

Aim: To examine the relationship between legacy leadership and nurse interns’ readiness for clinical practice and to test the moderating role of psychological safety. Background: The transition from nursing education to clinical practice is a critical period marked by gaps in readiness, limited self‐regulation, and increased patient safety risks. Leadership within clinical settings remains a key modifiable factor shaping this transition. Legacy leadership, grounded in mentorship, ethical modeling, long‐term professional development, and psychological safety have been proposed as facilitators of intern readiness. Their combined role remains underexplored in Saudi Arabia. Methods: A cross‐sectional predictive correlational design was used. A convenience sample of 178 nurse interns was recruited from four Saudi universities. Data were collected using a self‐administered questionnaire including the Legacy Leadership Scale, Nursing Practice Readiness Scale, and Psychological Safety Scale. Data were analyzed using descriptive statistics, Pearson correlation, an independent samples t ‐test, and hierarchical regression. All instruments demonstrated strong internal consistency. Results: Most participants (82.5%) reported high perceptions of legacy leadership ( M = 107.34, SD = 15.76; 85.9%). Readiness for practice was high ( M = 117.80, SD = 18.06; 84.1%); self‐regulation was the lowest domain (82.9%). Psychological safety was moderate‐to‐high ( M = 37.55, SD = 9.47; 76.6%). Legacy leadership showed a significant association with readiness for practice ( β = 0.757, R ² = 0.573, p < 0.001). Psychological safety did not significantly moderate this relationship. Conclusion: Legacy leadership showed the strongest association with readiness for practice and accounted for the largest proportion of explained variance within the regression model. Psychological safety did not function as a moderator. Its role within the leadership readiness relationship may warrant further investigation using alternative explanatory models. Implications for Nursing Management: Nursing managers should institutionalize structured mentorship development, ethical role modeling, and collaborative empowerment as core legacy leadership competencies within clinical internship frameworks to improve readiness outcomes.