Assuming your goal is mimicking the training data, you need some mechanism for drawing from the same distribution. AR happens to provide that -- it's a particular factorization of conditional probabilities which yields the same distribution you started with, and it's one you're able to replicate in your training data.

AR is not the only possible solution, but many other techniques floating around do not have that property of actually learning the right thing. Moreover, since the proposed limitation (not being able to think a long time about your response before continuing) is a byproduct of current architectures rather than a fundamental flaw with AR, it's not as obvious as it might seem that you'd want to axe the technique.