Background Artificial intelligence (AI) is increasingly applied in residential aged care (RAC) in recent years, yet a comprehensive understanding of its research landscape and emerging trends remains limited. This study aimed to map and synthesise the intellectual structure and development trajectory of AI research in RAC. Method A bibliometric analysis was conducted using CiteSpace on publications retrieved from the Web of Science. The search strategy was structured around two core concepts—‘AI’ and ‘RAC’—and limited to articles published between January 2010–April 2026, yielding 967 studies. Co-citation, keyword burst, and collaboration network analyses were performed to identify key research themes, influential references, and temporal trends. Results Publications increased markedly after 2020, accounting for 75% of studies, indicating rapid field expansion. Analysis on author defined keywords revealed a shift from early focus on ‘assisted living’, ‘administrative data’, and ‘risk factors’ to recent emphasis on ‘quality of care’, ‘primary care’, and ‘older people’. Cluster analysis identified a central focus on AI-driven predictive modelling (e.g., falls), alongside interconnected domains including health outcomes, dementia care, functional decline, and end-of-life care. Technology-oriented clusters, such as monitoring systems, sensor-based technologies, and smart care environments, reflect growing integration of real-time data and digital health solutions. Geographically, research output was dominated by the US and China, with increasing contributions from Europe and Asia-Pacific countries. Conclusions AI research in RAC is shifting towards integrating advanced methods with person-centred care. The growing focus on care quality and real-world implementation highlights the need for interdisciplinary collaboration and translation into practice.