AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis.

Introduction: Artificial Intelligence (AI) has made its way into every dimension of human life, and its impact is significant and multifaceted. Specifically, the effect of AI in nursing education has reshaped the healthcare system. However, this technological shift in nursing and the healthcare system still needs to be evaluated in multiple aspects to ensure the effective use of AI and to prepare future professionals. Methods: This PROSPERO-registered systematic literature review and meta-analysis explored the integration of AI literacy and competency within nursing curricula and the profession globally from January 2020 to June 2025. The study specifically aimed to: (1) examine the extent of AI integration within nursing curricula; (2) assess the awareness, attitudes, and readiness of nursing students, faculty, and practitioners toward AI; (3) evaluate the effectiveness of educational interventions designed to enhance AI literacy and competency; (4) identify ethical, institutional, and pedagogical challenges associated with AI adoption in nursing education; and (5) provide evidence-based recommendations for standardized and equitable AI education frameworks in nursing. Results: The review synthesizes evidence from 111 peer-reviewed articles, including 18 distinct quantitative studies, which have been further analyzed through meta-analytic techniques. PRISMA guidelines were followed to search for relevant articles and extract the required information. Meta-analysis reveals high levels of AI-related awareness (pooled estimate = 73%, 95% CI: 64-80%) and positive attitudes (71%, 95% CI: 63-78%) among various nursing groups. The implementation of AI-related skills remains highly variable (67%, 95% CI: 55-78%), especially in low-resource settings, which needs careful interpretation. Overall, meta-analysis findings highlight significant variations and reflect non-uniformity and disparities across regions, institutions, and nursing groups (students, staff, faculty). Conclusion: Thematic synthesis underscores the need for standardized AI education, tailored faculty development, and equitable access to digital tools. Although individual-level awareness and attitudes toward AI are promising, this review reveals a lack of institutional readiness, with many nursing programs lacking standardized curricula, faculty training, and infrastructural support. Moreover, findings emphasize the critical need for broader institutional and policy efforts to match individual enthusiasm with institutional capacity in preparing nurses for an AI-enabled healthcare landscape. Further, this review offers evidence-based recommendations for various stakeholders to ensure inclusive and future-ready nursing education. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD420251090108.