Tasks in architectural and interior design range from defining the building floor plans and ensuring desired functionality, to deciding furnishing styles and arrangement choices. The process of design, as a whole, has remained hard to master for computer-based optimization in general and for computational intelligence approaches in particular. Numerous attempts to tackle different subfields of this problem in a machine learning fashion have emerged over the last few years. In this paper, we present an overview of current advances of computational intelligence in architectural science with a focus on interior design. This is accompanied by the description of ongoing research towards the development of a commercial robust and scalable solution for automatic furniture arrangement.