Contract theory is the study of economic incentives when parties transact in the presence of information asymmetries. We augment classical contract theory to incorporate a role for learning from data, where the overall goal of the adaptive mechanism is to obtain desired statistical behavior. We consider applications of this framework to problems in federated learning, the delegation of data collection, and principal-agent regulatory mechanisms.