Abstract
With global population aging, the prevalence of multimorbidity among older adults has risen sharply. This growing complexity challenges traditional single-disease-oriented healthcare models, leading to fragmented care, increased polypharmacy risks, and poor clinical outcomes. Precision medicine, integrating genomic, phenotypic, and behavioral data, offers a promising avenue for individualized care in this context. Concurrently, artificial intelligence (AI) has emerged as a powerful enabler of precision medicine by facilitating large-scale data analysis, real-time risk prediction, and multimodal data integration. This review summarizes recent advances in the application of AI-enabled precision medicine for managing geriatric multimorbidity, providing a theoretical and practical framework for integrating AI-enabled care. It highlights the need for interdisciplinary collaboration, regulatory innovation, and equity-focused design to transform multimorbidity management in aging societies.