Artificial intelligence in nursing practice for older adults with dementia: A narrative review informed by bibliometric mapping and implications for nurse-led research

PURPOSE: This narrative review aimed to (1) map the global research landscape of artificial intelligence (AI) in dementia care, (2) characterize domestic Korean research, and (3) propose priority directions for nurse-led AI research. METHODS: International literature was retrieved from PubMed (January 2015 to December 2025; n=5,710) and analyzed using VOSviewer with the Leiden algorithm. Korean literature from RISS (n=265) was synthesized narratively. RESULTS: Publications increased substantially since 2015, with acceleration after 2024 driven by large language models. Five thematic clusters emerged: (1) care, daily living, and digital health; (2) aging and brain structure; (3) risk prediction and clinical data; (4) early screening and behavioral biomarkers; and (5) Alzheimer's diagnosis and deep learning. Four domains were most relevant to nursing: monitoring technologies, digital biomarkers, AI chatbots for caregivers, and clinical decision support systems. Korean research concentrated on emotional support robots with methodological limitations. CONCLUSION: Rigorous nurse-led trials with multidimensional outcomes are needed to establish AI's clinical value in dementia nursing.