I'm working on a task-oriented dialog product and things are going surprisingly well from a business standpoint. It turns out that existing techniques are sufficient to substitute some portion of commercial dialog interactions from human to machine mediated, with tremendous associated cost savings which exceed the cost of developing the automatic systems. Here's the thing that is puzzling: the surplus is so large that, as far as I can tell, it would have been viable to do this 10 years ago with then-current techniques. All the new fancy AI stuff helps, but only to improve the margins. So how come these businesses didn't appear 10 years ago?
I suspect the answer is that a format shift has occurred away from physical transactions and voice mediated interactions to digital transactions and chat mediated interactions.
The movement away from voice is very important: if we had to try and do this using ASR, even today, it probably wouldn't work. Fortunately, today you chat with your cable company rather than talking to them. That shift was motivated by cost savings: a human agent can handle multiple concurrent chat sessions more easily than multiple concurrent voice conversations. However it requires most of your customers to have a computer, smartphone, or other device rather than an old-school telephone.
The continuing dominance of e-commerce over physical stores is also a factor (RIP Sears). In e-commerce, human salespersons increasingly assist customers in transactions via live chat interfaces. Once again, what starts as a more effective way of deploying human resources becomes the vector by which automation increasingly handles the workload.
The end game here is that the number of people employed in retail goes down, but that their compensation goes up. That is because the machines will increasingly handle the routine aspects of these domains, leaving only the long tail of extremely idiosyncratic issues for the humans to resolve. Handling these non-routine issues will require more skill and experience and therefore demand higher compensation (also, an increasing part of the job will be to structure the torso of non-routine issues into something that the machines can handle routinely, i.e., teaching the machines to handle more; this is analogous to programming and will also demand higher compensation).
