It hasn't really, at least not in production. Academics are now publishing a lot of papers using Deep Learning or RL, but you won't usually see those in live systems.
In live systems, latency is usually more important than a "better" model - A model that takes milliseconds to make slightly better predictions is too slow when you're working on nano- to microsecond scales, often on specialized hardware. Really, the "AI" part is less important in HFT than you may think. It's often more system/infrastructure.
This is for HFT specifically, perhaps it has had more impact on longer time horizons, or something like portfolio management. My impression is (but I may be wrong) that there aren't that many people doing something in between HFT and much longer (minutes to days) time horizons, something like milliseconds to seconds. Maybe there is an opportunity there for some of the newer AI techniques.
In live systems, latency is usually more important than a "better" model - A model that takes milliseconds to make slightly better predictions is too slow when you're working on nano- to microsecond scales, often on specialized hardware. Really, the "AI" part is less important in HFT than you may think. It's often more system/infrastructure.
This is for HFT specifically, perhaps it has had more impact on longer time horizons, or something like portfolio management. My impression is (but I may be wrong) that there aren't that many people doing something in between HFT and much longer (minutes to days) time horizons, something like milliseconds to seconds. Maybe there is an opportunity there for some of the newer AI techniques.