Protein phosphorylation dynamically integrates environmental and cellular information to control biological processes. Identifying functional phosphorylation amongst the thousands of phosphosites regulated by a perturbation at a global scale is a major challenge. Here, we introduce “personalised phosphoproteomics”, an experimental and computational framework that links signalling with biological function by utilising human phenotypic variance. In this approach, individual subject phosphoproteome responses to interventions and corresponding phenotypes are measured in parallel. We applied this method to investigate the dynamic regulation of metabolism in human skeletal muscle responding to exercise and insulin by performing two independent studies. We quantified >11,000 phosphopeptides in human skeletal muscle biopsies responding to insulin and prior exercise. We also measured 245 skeletal muscle biopsies sampled from insulin sensitive and resistant subjects over time, in which we utilised data-independent acquisition to quantify >26,000 phosphopeptides. Personalised phosphoproteomics identified known as well as previously unidentified phosphosites on proteins involved in glucose metabolism. This includes a co-operative relationship between mTOR and AMPK, whereby mTOR directly phosphorylates AMPK on S377, for which we find a role in metabolic regulation. These results establish personalised phosphoproteomics as a general approach to investigate the signal transduction underlying complex biology.