Abstract
BACKGROUND: The rapid integration of artificial intelligence (AI) into healthcare demands that nurses not only develop technical competencies but also uphold strong professional values to maintain effective and ethical practice. While AI readiness is gaining attention, its relationship with nursing professionalism and self-efficacy remains underexplored. OBJECTIVE: To examine the relationship between nurses’ AI readiness and their self-efficacy, with a specific focus on the moderating role of professionalism within clinical practice settings. METHODS: A descriptive cross-sectional design was employed involving 278 staff nurses from three tertiary healthcare hospitals: one hospital in Kafr Elsheikh Governorate and two hospitals in Alexandria Governorate, Egypt. Data were collected using three validated instruments: the Nursing Profession Self-Efficacy Scale, the Artificial Intelligence Readiness Scale, and the Nurse Professionalism Scale. Pearson correlation, multiple regression, and path analysis were performed using SPSS v25 to examine the relationships among the study variables and to test the proposed hypotheses. RESULTS: The findings revealed that both AI readiness (β = 0.143, p = 0.017) and professionalism (β = 0.147, p = 0.014) were significant predictors of nurses’ self-efficacy. Path analysis confirmed direct effects of both variables on self-efficacy and supported the moderating role of professionalism. AI readiness and professionalism collectively explained 4.7% of the variance in self-efficacy. Nurses reported high levels of self-efficacy and professionalism, but moderate AI readiness, especially in ethical and visionary subdomains. CONCLUSION: Nurses’ self-efficacy is shaped by both their preparedness to use AI technologies and their professional values. Professionalism enhances the psychological impact of AI readiness, enabling nurses to adapt confidently in evolving healthcare environments. IMPLICATIONS OF THE STUDY: Nursing leadership and education should integrate AI literacy with professional development to build a confident, ethically grounded workforce capable of leveraging AI for improved care outcomes. CLINICAL TRIAL NUMBER: Not applicable.