It's important to keep in mind the exact quantity of "more practice". Current mechanisms of reinforcement learning are not very data-efficient, which means that

It's important to keep in mind the exact quantity of "more practice". Current mechanisms of reinforcement learning are not very data-efficient, which means that often humans will learn faster than bots. It will still allow bots to discover any unrealistic advantage they have over humans (e.g. faster micromanagement), but if the game is fair and experience to learn from is limited, humans may still prevail. To "beat" Atari games, AIs trained using reinforcement learning had to put in significantly more than the 10k hours one would expect a human to put in in order to become expert. So, AIs won't beat humans in tasks where training data is costly; however these cases are not interesting to researchers and hence you won't hear from the respective results.