Emerging multi-display infrastructures provide users with a large number of (semi-) public and private displays. Selecting what information to present on which display here becomes a real issue, especially when multiple users with diverging interests have to be considered. This especially holds for dynamic ensembles of displays. Therefore, automatic assignment strategies might be useful, if they are able to provide the required assignment precision. We claim that it is possible to define such strategies, and show that it is able to assist users in solving specific tasks in multi-display environments at least as effectively as conventional manual assignment. Our claims are based on user performance data collected in the scope of a comparison study.