This paper examines three trends in positioning, i.e. options for determining the location of a remote station in future communication standards, the transition from primary radar to secondary radar, and the integration of machine learning. While the first trend primarily concerns localization systems that are based on underlying communication infrastructure, the second trend relates more to proprietary approaches that are specifically designed for positioning. Apart from this, conventional concepts can be improved using artificial intelligence, e.g. to increase accuracy, to integrate results from multiple individual systems or to predict future trajectories.