Rl works on one of two things - (1) a literal set of rules for a system or (2) training data. The former matches perfectly to things like (most modern) math and games that have perfect sets of rules. Even things like physics and robotic where our rules/models are extraordinarily good, rl barely adds value. Move one step farther to chemistry or a complicated physics scenario like weather, and you are back almost entirely dependant on (2) data. Now there might be a few more domains with rigorous rulesets that haven't been explored fully (id bet with some effort programming might make some strides here, maybe something like circuit layout, maybe even law if folks decided to make a lean-like law scheme...) but the vast majority of problems AI is targeting are dependant on data.