Ageing is a multidimensional and heterogeneous process that progresses asynchronously across organ systems. Advances in multi-omics technologies have led to the development of diverse ageing clocks, including epigenetic, proteomic, metabolomic, and imaging-based models, which extend beyond estimating crude biological age to more precisely capture organ-specific ageing trajectories and predict age-related diseases and mortality risk. Population-scale studies demonstrate substantial within-individual variation in organ-ageing rates, showing that accelerated ageing in specific organs and increased numbers of aged organs markedly contribute to systemic dysregulation and elevated mortality risk. Multi-organ-ageing clocks further highlight the role of organ crosstalk networks, such as cardiovascular-pulmonary-cerebral interactions, in shaping healthspan and survival. Building on these insights, we propose a conceptual artificial intelligence (AI)-driven multi-omics health platform that integrates clinical data, imaging, wearable sensors, and organ-specific ageing clocks to enable continuous monitoring of biological age and early risk detection. This platform supports stratified management, whereby individuals with mild ageing may benefit from lifestyle-based interventions, while those with accelerated or multi-organ ageing receive personalised pharmacological and clinical strategies. Together, multi-omics ageing clocks and AI-enabled analytics provide a transformative framework for understanding human ageing, shifting from single-organ assessment to network-level evaluation and precision anti-ageing interventions. These advances lay the groundwork for a scalable national health ecosystem aimed at extending healthy lifespan and reducing population-wide mortality risk.
