Background: Nursing students' acceptance and usage of AI are crucial for embracing and implementing the technology in nursing practice in the future. However, there is a lack of literature to examine the factors affecting AI usage intention among nursing students. Aim: This study examined a hypothesized model based on the unified theory of acceptance and use of technology (UTAUT2). The intention to use AI mediates the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit on nursing students' AI usage. Gender was expected to moderate these relationships. Methods: Employing a multicenter cross-sectional approach, this study was conducted across three Saudi universities between September and October 2023 with 500 undergraduate nursing students. The variables were measured using a self-report questionnaire originally developed based on UTAUT2. The internal consistency of the latent variable items and convergent, divergent, and construct validity were assessed. Structural equation modeling was conducted to test the hypothesized model. Results: Performance expectancy (beta = 0.235, p = .004), facilitating conditions (beta = 0.233, p = .026), hedonic motivation (beta = 0.371, p < .001), and habit (beta = 0.458, p < .001) influenced AI usage intention, which significantly affected actual AI usage (beta = 0.702, p < .001). Behavioral intention mediated the relationship between AI usage in nursing education and performance expectancy (beta = 0.165, p = .007), motivation (beta = 0.261, p = .001), and habit (beta = 0.321, p = .002). Gender moderated the effects of behavioral intention (Delta beta = 0.613, p = .005) and facilitated conditions (Delta beta = -0.440, p = .023) on AI usage. Conclusions: The findings will help stakeholders promote AI usage among future nurses. They highlight the need for interventions and strategies to enhance the perceptions of AI's benefits, resource availability, and individuals' enthusiasm and usage habits.