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 'personalized phosphoproteomics', a combination of experimental and computational analyses to link signaling with biological function by utilizing human phenotypic variance. We measure individual subject phosphoproteome responses to interventions with corresponding phenotypes measured in parallel. Applying this approach to investigate how exercise potentiates insulin signaling in human skeletal muscle, we identify both known and previously unidentified phosphosites on proteins involved in glucose metabolism. This includes a cooperative relationship between mTOR and AMPK whereby the former directly phosphorylates the latter on S377, for which we find a role in metabolic regulation. These results establish personalized phosphoproteomics as a general approach for investigating the signal transduction underlying complex biology.