The National Health Service is under increasing pressure due to mismatches between workforce capacity, infrastructure and the evolving needs of population health. These issues have led to rising inefficiencies, structural imbalances and service misalignments relative to actual health demand. Addressing these challenges requires an integrated, data-driven planning approach that enables better resource alignment, targeted investment in critical areas and productivity optimisation through a whole-of-system lens. A phased strategy – combining immediate recovery of service capacity with a long-term transformation plan – is essential. By leveraging artificial intelligence (AI)-enabled system intelligence and predictive analytics, this article presents a detailed case study analysis to support sustainable, value-based healthcare tailored to population needs.