AI literacy in nursing education: Building workforce readiness for safe and ethical integration into practice

To assess nursing faculty members' AI literacy, ethical awareness and perceived readiness for integrating AI into nursing education and to identify key predictors of readiness.

The integration of artificial intelligence (AI) in healthcare is advancing rapidly, necessitating foundational AI competencies among nurses. However, nursing faculty often lack sufficient literacy and ethical readiness to effectively prepare students for AI-enhanced clinical environments.

A mixed-methods explanatory sequential design was used. A cross-sectional survey of 46 nursing faculty at a Saudi university assessed AI literacy, ethical awareness and perceived readiness. Descriptive statistics, t-tests, ANOVA (η² = 0.23) and regression analysis were applied. Twenty follow-up interviews were thematically analyzed using Braun & Clarke's six-phase approach. Data strands were integrated to enhance interpretive depth.

AI literacy (M = 3.52, SD = 0.71) and ethical awareness (M = 3.74, SD = 0.67) were moderate, while perceived readiness was lower (M = 3.24, SD = 0.82). Faculty with prior AI exposure reported significantly higher readiness (t = 3.48, p = 0.001, Cohen's d = 1.00). Regression analysis identified AI literacy (β = 0.53, p < 0.001), prior exposure (β = 0.36, p = 0.005) and ethical awareness (β = 0.31, p = 0.021) as significant predictors of readiness (R² = 0.45). Qualitative themes included: lack of formal training, ambivalence about integration, ethical concerns, institutional resource challenges and recognition of AI's potential.

Despite conceptual awareness, nursing educators reported limited readiness for AI integration due to training gaps and institutional barriers. Structured development programs and policy reforms are essential to enhance workforce readiness and ethical implementation of AI in nursing education.