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Utility-based control (UBC) hasn't been widely adopted for commercial game AI. Some of the reasons for this are that UBC is perceived to be: (1) resource intensive, (2) difficult to design complex behaviours with, and (3) difficult to scale for use in complex environments. This paper investigates these perceptions to see if UBC is suitable for controlling the behaviour of non-player characters in commercial games. The investigation compares agents using a UBC system against two control systems that are more frequently used in commercial games: finite state machines (FSMs), considered a simple control system, and goal-oriented action planning (GOAP), considered a complex control system. We present a feasibility study which suggests that: (1) UBC is more resource intensive than FSMs but less so than GOAP; (2) it is reasonably simple to create complex behaviours using UBC; (3) UBC doesn't scale as well as FSMs or GOAP for use in complex environments.