Digital organisms (DOs) model the basic structure and development of natural organisms to create robust, scalable, and adaptive solutions to problems from different fields. The applicability of DOs has been investigated mainly on a few synthetic problems like pattern creation, but on a very limited number of real world problems, e.g., the creation of architectural structures. In this paper the potential of DOs for learning to play the game of Go is demonstrated. Go has been chosen for its high complexity, its simple set of rules, and its pattern-oriented structure. A DO is designed, which is able to learn to play the game of Go by means of artificial evolution. The DO is evolved against three computer opponents of different strength on a 5×5 board. Specifically, we are interested in the DO's scalability, when evolved to play on the small board and transferred to a larger board without any external adaptations.