The field of model reduction has evolved continuously over the last 15 years, with many seminal contributions and methodologies that overcome barriers that were previously considered to be almost impossible. Initially, most of the attention has been for linear problems, where many issues have been resolved, so that the state of the art for such problems is now quite mature. Similar developments in other areas of model reduction, such as parameterized and nonlinear problems, as well as in situations coping with uncertainty, are expected. In several of these areas, researchers are currently obtaining promising results by using newly developed methods, sometimes inspired by other fields of mathematics or by developments in data science. The range of feasible mathematical technologies is vast, and researchers are exploring many of these right now. The formation of a community that interacts via a pan-European network will have a very positive effect on the development of new techniques, so that there is a high level of confidence that the Action can adequately address the challenge.