<![CDATA[Community and home nursing care are increasingly central to health systems in response to population ageing, rising chronic disease burden, and the need to reduce avoidable hospital utilization. Artificial intelligence (AI) has emerged as a technological innovation with potential to support nursing practice in non-hospital settings. However, the role and implications of AI within community and home nursing care have not been systematically synthesized. This systematic literature review aimed to examine how AI supports community and home nursing practice, identify the types of AI technologies applied, and analyze their reported outcomes and implications for nursing care. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 237 records were identified through electronic database searches. After duplicate removal and screening, 38 full-text articles were assessed for eligibility, and 15 studies were included in the final qualitative synthesis. The included studies, published between 2024 and 2026, encompassed diverse methodological designs and were conducted in community-based, home health, telemonitoring, and mobile nursing contexts. The findings indicate that AI technologies primarily include machine learning–based predictive models, clinical decision support systems, telemonitoring platforms, digital wound assessment tools, and large language model–supported analytics are used to enhance risk prediction, remote monitoring, chronic disease management, and care coordination. Across studies, AI was associated with improved early detection of clinical deterioration, enhanced workflow efficiency, and potential reductions in hospital admissions. Nevertheless, effective implementation depended on nurse engagement, system usability, digital literacy, and organizational support. AI demonstrates substantial potential to strengthen community and home nursing care when integrated within a human-centered and ethically grounded framework that preserves professional nursing judgment.]]>
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