Advancing Nursing Through Artificial Intelligence: A Systematic Literature Review of Current Evidence.

Artificial intelligence (AI) is increasingly being explored within nursing practice, education, and workforce-related contexts; however, the scope and strength of the supporting evidence remain variable. This systematic review aimed to synthesize empirical evidence on AI-driven interventions in nursing and to examine their reported associations with clinical, educational, and workforce outcomes. The review followed PRISMA 2020 guidelines. A systematic search of PubMed, Scopus, Web of Science, and CINAHL was conducted for peer-reviewed English-language studies published between 2018 and August 2025. Eligible studies examined AI-based interventions applied in nursing practice, nursing education, or nursing workforce settings. Eleven studies met the inclusion criteria, comprising randomized controlled trials, quasi-experimental studies, and retrospective evaluations; non-empirical sources were used only to contextualize findings. Across the included empirical studies, AI-based interventions were reported to be associated with improvements in selected outcomes, including patient self-care and clinical indicators, learner engagement and confidence in nursing education, and aspects of nurse well-being and organizational efficiency. However, findings were heterogeneous, largely derived from small samples and short follow-up periods, and quantitative reporting was inconsistent across studies. Overall, the available evidence suggests that AI is currently applied as an assistive tool supporting specific nursing tasks rather than replacing professional judgment. While AI applications in nursing show promise across several domains, the evidence base remains limited and context-dependent, highlighting the need for further methodologically rigorous and longitudinal research before broader implementation can be confidently supported.