Spatial load forecasting methodologies spatially allocate expected electricity demand growth in a study area. In the last decades, this kind of forecasting has been applied to backup traditional transmission and distribution grid expansion studies using publicly available, georeferenced information. Recently, a growing number of studies materialized the availability of computational intelligence tools to improve electricity network planning. Planners can use spatial load forecasting outputs to build accurate scenarios with high spatial resolution that allow for better investment decisions and eventually drive down network expansion costs. Furthermore, results of spatial load forecasting can help power system planners to comply with new deregulation and decarbonization policies, while addressing emerging challenges in power system planning. This paper provides insights in recent spatial load forecasting developments and emerging data-driven applications that will render modern power system planning.