Like self-driving cars, it's not enough to outsmart AI on one move, it's necessary to outsmart on AI with positive expected value over all the moves you are confident enough to weight in on.
AlphaGo (and, presuably, any AI system with a remotely simmilar means of operation) can output a score for each move. Actually, AG can output 2 scores: win percentage and branches explored.
You can use the relative scores to decide when to overrule the AI. Eg, if move A has a 50.1% win chance with 2k branches explored, and B has a 50.2% chance with 1.9k branches explored, I would go with the opinion of an expert human, as AG thinks the moves are essentially equal.
Self-driving cars is a terrible comparison, especially since the state of the art right now is that the best human drivers far outpace the best AI driving, in both skills and flexibility.
Plus, you only have to outsmart the car AI once to 'win' - e.g. just override one 'drive into the highway barrier' or 'run over that pedestrian' AI mistake.
You can use the relative scores to decide when to overrule the AI. Eg, if move A has a 50.1% win chance with 2k branches explored, and B has a 50.2% chance with 1.9k branches explored, I would go with the opinion of an expert human, as AG thinks the moves are essentially equal.