This technology allows a (very) large number of experiments to be performed, allowing explorative screening. Cell-based systems are mainly used in chemical genetics where large, diverse small molecule collections are systematically tested for their effect on cellular model systems. Novel drugs can be found using screens of tens of thousands of molecules, and these have promise for the future of drug development. 
Beyond drug discovery, chemical genetics is aimed at functionalizing the genome by identifying small molecules that acts on most of the 21,000 gene products in a cell. High-content technology will be part of this effort which could provide useful tools for learning where and when proteins act by knocking them out chemically. This would be most useful for gene where knock out mice (missing one or several genes) can not be made because the protein is required for development, growth or otherwise lethal when it is not there. Chemical knock out could address how and where these genes work.
Further the technology is used in combination with RNAi to identify sets of genes involved in specific mechanisms, for example cell division. Here, libraries of RNAis, covering a whole set of predicted genes inside the target organism's genome can be used to identify relevant subsets, facilitating the annotation of genes for which no clear role has been established beforehand.
The large datasets produced by automated cell biology contain spatially resolved, quantitative data which can be used for building for systems level models and simulations of how cells and organisms function. Systems biology models of cell function would permit prediction of why, where and how the cell responds to external changes, growth and disease.