It's still a game that can be described in terms of clear state-machine rules. The real challenge for AI is making sense and acting in the real world, which can't be described in such way. I consider advances in self-driving cars much more interesting in that sense - even if, even there, there are at least some rule-based constraints that can be applied to simplify the representation of the "world state".
Beating the average human Go player was probably accomplished decades ago, whereas it's not even clear if we're safer than the average human driver (under all conditions).
These tasks are just wildly different, and yes I think it's basically all due to the fact that Go's state is so easily represented by a computer, and the goal is so concrete.
The real problem is dealing with all the edge cases. Think of this edge case. You pull up to a red light, a guy with a gun starts running at your car in a manner you perceive to be threatening.
You as a human are most likely going to step on the gas and get the hell out of there saving yourself, at some risk of causing a traffic accident.
The car will just sit there till the light turns green while the windows get shot out and you get dragged out of the car.
Thing is, it wasn't. Go AIs were on the level of amateurs (and amateurs could win) only a two years ago.
edit. 'Decades ago', i.e. in 1990s, amateurs would crush the AIs. https://en.wikipedia.org/wiki/Computer_Go#Performance
Anyway Marazan already pointed that out, but any computer system is a state machine, with 2^N states where N is the number of bits the machine can flip anywhere in its system (RAM, registries, disk, etc.).