I do foresee a future in which a trader can accomplish a lot more than he/she can today using AI. So in the future as the per trader efficiency increases, the number of traders required will most probably decline, unless there is a dramatic increase in trading volume that cannot be matched by the then state of the art AI.
This is essentially what's happening today with X.ai, Facebook messenger and the like. Sure the logic involved in booking air tickets for a group of 5 over 10 conversations isn't as complicated as the rich business logic of a trade, but 5 years back Facebook messenger would've seemed almost impossible, just like the trading business logic seems impossible to do with AI today.
On the other hand, the technology advances needed to transform the tools into standalone actors are not merely a matter of scaling current technology. Especially, the creation of training datasets is a problem for which we currently have no solution, that's why we fall back on human trainers (mturk, etc). That's why a solution to a problem with no clear, bounded model and no easy dataset seems out of reach.
A trader is not necessarily a sales or a broker, though. Nor is he a quant, or a dev. People rarely imagine how many different jobs are involved in the trading job, and how rich the business logic is. At my shop, traders are the piece that connects all of the jobs in the value chain.
I believe, currently, the business logic can be improved locally by learning systems (and it is), but there is no public example of an industrial learning application encompassing a scope comparable to what the usual trading desk handles. Sure, there are many inefficiencies ; traders work on heuristics, afterall. But I don't believe we have the necessary horizon to aptly predict the end of traders, because I don't see how we could make AIs with a better efficiency.