Autonomic computing is a promising approach to the problem of effectively managing large complex software systems such as database management systems (DBMSs). In order to be self-managing, an autonomic DBMS (ADBMS) must understand key aspects of its workload, including composition, frequency patterns, intensity and resource requirements. It must therefore use and maintain different characterizations, or models, of the workload to support its various kinds of decision-making. Our research into various aspects of ADBMSs has led us to develop a number of different workload models. In this paper, we examine the importance of workload models to ADBMSs. We discuss the types of workload models needed by ADBMSs and describe examples from our research. We then outline the requirements for an infrastructure to develop and maintain the workload models needed by an ADBMS.