Comment by dgacmu

We do semi-automated analysis of imagery of things like utility right-of-ways and it's pretty scalable. We triage the vast majority of images automatically and then surface a small subset to human experts to review, but it's much, much faster than having the experts be in the field, while having high coverage. (Most images are really boring.)

And in most cases of inspection, you need to look at the stuff anyway, so any cost reduction is very welcome. And if you do increase the total coverage volume while reducing human time, you get a double benefit of being able to provide more granular information, either in time or in space, which can often be useful.

(And as a commenter below notes - this all works pretty well with several year old CNNs. We use a limited amount of image-LLM stuff to surface things zero-shot, but a lot of what we end up doing is a very conventional classifier with a lot of engineering work to make it very fast for the experts to see only the important things.)