Artificial Intelligence Readiness in Nursing: A Scoping Review of Knowledge, Attitudes, Practice, and Emerging Evidence on Patient Safety Culture

Background: Artificial intelligence (AI) is increasingly integrated into nursing practice, yet nurses often demonstrate low to moderate AI knowledge, mixed attitudes, and inconsistent practice behaviors. Although individual studies have examined these domains, no review has comprehensively examined AI-related knowledge, attitudes, and practice (KAP) together with the emerging evidence on patient safety culture among nurses. This gap is significant because safe AI adoption in nursing depends on both technical competence and a strong safety culture across diverse clinical settings. Objective: To systematically map international evidence on nurses’, nursing students’, and other included participants’ AI-related KAP, and to examine how these factors may relate to patient safety culture. Because several eligible studies included multidisciplinary samples in which nurse-specific quantitative data were not reported separately (China, Bangladesh, Pakistan, and three studies from the Kingdom of Saudi Arabia [KSA]), only studies with extractable nurse-specific results were used to inform nurse-focused conclusions, and multidisciplinary findings were not attributed solely to nurses. Methods: This scoping review followed Arksey and O’Malley’s framework and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Searches of PubMed, CINAHL, Scopus, Web of Science, and ScienceDirect (2021–2026) identified studies examining AI-related perceptions among nurses and other healthcare participants when nurse-specific data were reported separately or extractable. Data extraction and narrative synthesis were conducted using Joanna Briggs Institute guidance. Results: Ten studies met the inclusion criteria and were included in the final review. Studies from China, Bangladesh, Pakistan, the KSA, Turkey, and the United Arab Emirates showed variable AI knowledge but predominantly positive attitudes. Ethical concerns—privacy, job displacement, and reduced empathy—were common. Younger age, higher education, and prior AI exposure were associated with more favorable perceptions. Nurses across regions emphasized the need for structured AI training. Only one study examined patient safety culture, and it reported that AI knowledge and attitudes significantly predicted patient safety culture, with attitude showing the stronger effect. However, because this evidence comes from a single cross-sectional study conducted in a multidisciplinary sample without nurse-specific results, it is insufficient to establish causal conclusions, and its findings cannot be generalized specifically to nurses. Conclusions: Nurses are generally receptive to AI but lack sufficient knowledge, training, and organizational support for safe implementation. Preliminary evidence suggests a positive association between AI-related knowledge, attitudes, and patient safety culture, but this relationship remains uncertain due to the extremely limited evidence base and the reliance on evidence that is not exclusively nurse-specific. Available studies indicate generally favorable attitudes toward AI alongside variable knowledge, limited formal training, and persistent ethical and organizational concerns, with only one eligible cross-sectional study linking these factors to patient safety culture. The conclusion regarding this association should not be attributed exclusively to nurses because the patient safety culture evidence was derived from a multidisciplinary sample. Future research should explore how AI competencies may interact with safety-related behaviors and organizational systems. Strengthening AI training, ethical guidance, and organizational support remains essential for safe adoption.