I think this assessment of what's "typical" may just be based on posturing. For some reason you can't brag about training a relatively shallow neural network (is efficiency not valued in this field?).

My counter-assessment is that the space of problems you solve just by making your NN deeper is very small. Such problems clearly exist, but I've seen few compelling examples outside of image classification.