The AI is based on the minimax algorithm [1]. Because of the way Minimax works, the only way for a possible next move to be designated a "win" is if it is a guaranteed win. (The tree is (effectively) fully explored, and the opponent is given the benefit of the doubt in the face of incomplete information.) So, if there are multiple such winning moves, and care is not taken to distinguish the "magnitude" of the win, the AI will choose one arbitrarily.

I suppose that, in Hive, it is more likely that a path to a win is longer rather than shorter. Hence, when my AI was arbitrarily choosing "winning" moves, it statistically chose those that drew the game out.

[1] https://en.wikipedia.org/wiki/Minimax

But once you have guaranteed winning moves, why not pick the shortest one available (in terms of turns)?

Yes, that's what I did after I found the design flaw which effectively threw that information away.

Usually it's because as it searches the move tree, it finds ways for the opponent to maximize their own winning probability and so has to hedge against that. In minimax games sometimes the evaluator finds a long chain of moves that leads to a win, and once it finds that, doesn't necessarily bother trying to find a shorter one. It can be frustrating to tune that out.

That happens if the winning probability of the other move is 1 as well.

maybe he's defining a "winning move" as something with > 50% chance of winning