When he retired a few years ago, most of that was gone. The attorneys and paralegals were still required, there was a single receptionist for the whole office (who also did accounting) instead of about one for each attorney, and they'd added an IT person... but between Outlook and Microsoft Word and LexisNexis and the fileserver, all of those jobs working with paper were basically gone. They managed their own schedules (in digital Outlook calendars, of course), answered their own (cellular) phones, searched for documents with the computers, digitally typeset their own documents, and so on.
I'm an engineer working in industrial automation, and see the same thing: the expensive part of the cell isn't the $250k CNC or the $50k 6-axis robots or the $1M custom integration, those can be amortized and depreciated over a couple years, it's the ongoing costs of salaries and benefits for the dozen humans who are working in that zone. If you can build a bowl screw feeder and torque driver so that instead of operating an impact driver to put each individual screw in each individual part, you simply dump a box of screws in the hopper once an hour, and do that for most of the tasks... you can turn a 12-person work area into a machine that a single person can start, tune, load, unload, and clean.
The same sort of thing is going to happen - in our lifetimes - to all kinds of jobs.
I recall the mine water pump had a boy run up and down a ladder opening and closing steam valves to make the piston go up and down. The boy eventually rigged up a stick to use the motion of the piston to automatically open and close the valves. Then he went to sleep while the stick did his job.
Hence the invention of the steam engine.
Condensing the workforce as you describe risks destroying redundancy and sustainability.
It may work in tests with high performers over short dutations but may fall under over longer terms, with average performers, or with even a small amount of atrition.
Having cog number 37 pick up the slack for 39 doesn't work with no excess capacity.
Complete aside, just because you brought up this thought and I like the concept of it:
My mom trained professionally as a secretary in the 1970s and worked in a law office in the 1980s; at that point, if you were taking dictation, you were generally doing longhand stenography to capture dictation, and then you'd type it up later. A stenotype would've been a rarity in a pre-computer office because of the cost of the machine; after all, if you need a secretary for all these other tasks, it's cheaper to give them a $2 notebook than it is a $1,500+ machine.
My observation so far has been that executive leadership believes things that are not true about AI and starts doing the cost-cutting measures now, without any of the productivity gains expected/promised, which is actually leading to a net productivity loss from AI expectations based on hype rather than AI realities. When you lose out on team size, can't hire people for necessary roles (some exec teams now won't hire unless the role is AI related), and don't backfill attrition, you end up with an organization that can't get things done as quickly, and productivity suffers, because the miracle of AI has yet to manifest meaningfully anywhere.
AI alone can't do that, even if you make the weakest link in the chain stronger, there are probably more weak links. In a complex system the speed is controlled by the weakest, most inefficient link in the chain. To make an organization more efficient they need to do much more than use AI.
Maybe AI exposes other inefficiencies.
I worked on both - my skillset went from coding pretty bar charts in SVG + Javascript to configuring Grafana, Dockerfiles and Terraform templates.
There's very little overlap between the two, other than general geekiness, but thanks I'm still doing OK.