We have been here before (sort of)
The cash machine, the spreadsheet and desktop publishing were all meant to end whole jobs. What actually happened to the people in the room, and the one part of the story that usually gets left out.
What the evidence says 4 min read
Every few decades a machine turns up that is going to end a job, and every time, somebody writes the obituary early. It is worth looking at a few of those obituaries, because the history is more useful than either “it’ll be fine” or “it’s different this time”, which are the only two things anyone ever says about it.
Three stories, then the part people leave out.
The cash machine and the bank teller
Cash machines arrived in the 1970s and spread for decades. In the US their number quadrupled to about 400,000 between 1995 and 2010. Bank tellers, whose job was largely handing out cash, should have been finished.
They weren’t. The economist James Bessen found that US teller jobs actually rose, from about 500,000 in 1980 to about 550,000 in 2010. The mechanism is the interesting bit. Cash machines made a branch cheaper to run, so each branch needed fewer tellers, down by more than a third between 1988 and 2004. But because branches were cheaper, banks opened more of them: urban branches rose by more than 40%. And the tellers who were left did less counting and more talking. Loans, accounts, “have you thought about a credit card?”. The job became a sales job with a till attached.
On this site, bank tellers score 42. The counting and cash-handling tasks are still the most exposed. That has been true since 1975.
The spreadsheet and the bookkeeper
VisiCalc arrived in 1979 and did in seconds what a bookkeeping clerk did in a week: recalculate a whole ledger when one number changed. NPR’s Planet Money ran the numbers: since about 1980, some 400,000 bookkeeping and accounting clerk jobs in the US went away. Over the same period about 600,000 accountant jobs were added.
So the spreadsheet didn’t shrink accounting. It made accounting cheap, and when something gets cheap people buy a lot more of it. Businesses that used to do their numbers once a year started asking “what if?” every afternoon. Somebody had to ask the questions, and that somebody was an accountant.
The split still shows up in the data. Accounting and bookkeeping clerks score 36 here. Accountants score 49. Same field, very different amounts of the job that a machine can reach.
Desktop publishing and the typesetter
In the early 1980s, getting words onto a printed page took a small army of specialists: typesetters, paste-up artists, camera operators, plate makers. At their peak there were around 4,000 typesetting firms across North America. Then the Mac, PageMaker and the laser printer turned up, and graphic designers began setting their own type.
Most of those typesetting firms are gone. But “designer” became one of the most common creative jobs going, and the designer’s job quietly absorbed four or five of the old specialist jobs into one person with a mouse. The work didn’t vanish. It moved onto a different desk and got a new name. (Fun footnote: “desktop publisher” became a job title of its own, and the US government now expects it to shrink by 14% over the next decade. The machine that ate typesetting is now being eaten.)
The part people leave out
Here’s where the cheerful version of this story usually stops. It shouldn’t.
The teller story had a second act. After 2010, mobile banking did what the cash machine couldn’t: it kept people out of the branch entirely. Branches started closing, and the US Bureau of Labor Statistics now projects teller jobs to fall 13% between 2025 and 2035. The same job can survive one machine and lose to the next.
“The field grew” is not the same as “the people were fine”. The 400,000 bookkeeping clerks who lost their jobs were not, in the main, the same people as the 600,000 new accountants. Some retrained. Many didn’t. A job category recovering is not the same as a person recovering, and the gap between the two is where the hardship lives.
It was slow. Each of these took decades. People had time to retire out of the old job and be trained into the new one. Whether today’s tools arrive on that timescale is a genuine open question, and nobody honestly knows the answer.
So what do these stories actually teach?
Three things, and none of them is “relax”.
- Machines take tasks, and jobs reshuffle around what’s left. That’s why every score on this site is built from tasks, not job titles. The teller kept the conversation and lost the counting.
- Cheaper often means more. When a machine makes something cheap, demand can grow enough to create more work than it destroyed. It doesn’t always. But it happens often enough that “fewer tasks means fewer jobs” is not a law of nature.
- The winners were the people nearest the new work. Tellers who could sell. Bookkeepers who could advise. Typesetters who learned the Mac. If you want to know which way to lean, look up your job and see which of your tasks are the ones the machines like. Then lean the other way.
We have been here before. Sort of. The honest version is that we’ve been here several times, it went better than predicted for the jobs and worse than the averages suggest for some of the people, and it took long enough that most of them could adjust. That last part is the bit worth watching.
What this article is built on
- Working Paper 140, Generative AI and Jobs2025 index
International Labour Organization · CC BY 4.0
- ISCO-08ISCO-08
International Labour Organization · CC BY 4.0
Every source on the site, with its licence, is on the methodology page · data 0.8-observed-use
The jobs in this article
-
Exposed: Gradient 3Written profile Bank teller AI could take a fair chunk of five of the six tasks: crediting accounts, paying bills, changing currency and balancing the till. That gives it the lowest score of the twenty. 42 holds up 67 AI helps 54 AI does it 35.6 Hands-on -
Exposed: Gradient 4ISCO 4311 Accounting and bookkeeping clerks AI could take a fair chunk of all five tasks, from sending bills and statements to recording, summarising and checking financial data. 36 holds up 75.5 AI helps 70 AI does it 10.4 Hands-on -
Exposed: Gradient 3Written profile Accountant AI could take a fair chunk of half the eight tasks, led by preparing financial statements and designing costing systems. Auditing the books and investigating fraud or insolvency are mostly out of its reach. 49 holds up 73 AI helps 54 AI does it 13.6 Hands-on -
Exposed: Gradient 2Written profile Graphic designer AI could take a fair chunk of six of the ten tasks, led by making images and animations, forming concepts and preparing layouts. Haggling over designs with clients and overseeing production are furthest from its reach. 51 holds up 64 AI helps 49 AI does it 22.4 Hands-on -
Exposed: Gradient 1ISCO 7321 Pre-press technicians Laying out images and text on screen and checking proofs are where AI could take a fair chunk. Making printing plates and preparing cylinders it barely touches. 62 holds up 73 AI helps 31 AI does it 30.5 Hands-on
Read next
What the evidence says 5 min read
Truck drivers hand more work to AI than programmers do. Hardly any of them use it.
In Anthropic's usage data, truck driving tops our twenty jobs for work handed to AI. It also barely shows up. Why the thinnest slices look the most automated, and what to read first.
What the evidence says 5 min read
Seven in ten expect job losses. That is not what we measure.
Pew asked people in 37 countries what AI will do to work. In 34 of them, most expect fewer jobs. Here is what that finding is evidence of, and what it isn't.
Choices 4 min read
Where do apprentices come from now?
The tasks AI does best are often the ones juniors learned on, and young workers in exposed jobs are already being hired less. If nobody climbs the first rung, who reaches the top?