I dunno, I worked in an Amazon Warehouse for a year part-time (and a couple of weeks full-time when in-between jobs) --- on one occasion, I pulled up to a bin full of non-descript cardboard boxes near where a group of trainees were working their way through, grabbed one box, spun it around for the six-sided box check, scanned it, confirming it was the right one, and before I could move on to my next pick, a trainee asked, "How did you know that was the right box?", which required a several minute explanation of how the item description and the slight differentiations of the boxes led to that conclusion.
The big win would be training the folks doing stowing to not create such situations and to put markedly different things in each rainbow bin.
The "Markedly Different things" in each bin was a big Amazon Warehouse advance in warehousing. Traditionally - things that were "alike" were put on shelves/bins - but (according to Amazon) it was far more efficient for pickers (at least back in the day - may have changed since then) to have random things on shelves located near each other to allow for equal access to popular items by pickers.
This would be a more convincing take if reasoning LLMs didn't already exist. Given the growth in capability over the last few years alone nothing about your description "several minute explanation of how the item description and the slight differentiations of the boxes" seems beyond an artificial intelligence to solve by the time humanoid robots would be ready to physically traverse a warehouse.
Your last point is also interesting given perhaps a robot is more amenable to such instruction, thus creating cascading savings. Each human has to be trained, and could be individually a failure. Robot can essentially copy its "brain" to its others.
Or likely more accurately, download the latest brain trained from all the robot's aggregate experiences from the amazon hivemind hq