AI Automation

For four of these six jobs, you should hire a person.

Automation maths is local. Every payback figure you have been shown was worked out somewhere people are paid four or five times what they are paid here, and at Indian salaries the same sum comes out the other way. Here is the formula, and here is where it stops working.

Automation replaces tasks, and whether a task is worth replacing depends entirely on what that task costs locally.

tasks, not jobs

MeasuredAutor’s task-based account of what automation actually displaces. The framework is his; the local conclusion below is ours.

The same build, the same saving, two wage levels: payback moves by an order of magnitude.

19 months vs 2

AssumedWorked below on salary figures we picked and labelled. Put your own payroll in — the point is the size of the swing, not our numbers.

Which two of the six clear it comfortably.

2 of 6

AssumedReasoned from the formula, using our assumed inputs. Not a survey of outcomes across businesses — we have not run one, and this conclusion moves if your volumes differ.

The Luddites are used as an insult now, which is convenient for anyone selling machinery. What they actually did was more precise than the insult allows: they broke particularframes — the ones producing cheap goods with unskilled labour — and left others alone.2 Their objection was not that machines existed. It was about what was going to happen to the price of their work. On that narrow point they were correct.

Keep the useful half of that and throw away the rest. The useful half is that the sum only works out in a particular place, at a particular price of labour, and moving it somewhere else changes the answer.

Automation does not replace jobs. It replaces tasks, and whether a task is worth replacing depends on what that task costs where you are standing.1 Every glossy payback figure you have been shown was computed in a place where the person doing that task is paid several times what they are paid here. That is not a small adjustment. It flips the answer.

The formula, which fits on one line

You need four numbers, and you already have three of them.

  • S— what the person costs you a month, fully loaded. Not the salary. Salary plus everything.
  • f— the fraction of that role the automation actually takes. Be honest and be pessimistic. It is never all of it.
  • R— what the automation costs to run each month. Licences, messages, hosting, the person who fixes it when it breaks.
  • B— what it costs to build, once.

Monthly saving is f × S − R. Payback in months is B ÷ (f × S − R). That is the whole model, and it is enough to kill most proposals in about ninety seconds.

The same build, two countries

Numbers here are mine and made up. Replace them.

Say a back-office person costs twenty-five thousand a month, fully loaded. Say the automation genuinely takes sixty per cent of what they do, which is generous. Say it costs two thousand a month to run and two and a half lakh to build.

Saving is fifteen thousand minus two thousand, so thirteen thousand a month. Two and a half lakh divided by thirteen thousand is about nineteen months.

Now do it where the same role costs the equivalent of three lakh a month. Sixty per cent of that is one lakh eighty. Take off the same two thousand running cost and the saving is one lakh seventy-eight thousand a month. A two and a half lakh build pays back in under two months.

Same tool. Same code. Same vendor deck. Nineteen months against two. Every case study you have been sent was written in the second column.

A nineteen-month payback is not a bad investment. It is a bet that nothing about your business changes for nineteen months, which is a much braver bet than it sounds.

money saved, adding upmonthswhat the build cost — ₹2.5 lakhhigh-wage market — pays back in 2₹25,000 a month — pays back in 19salaries, build cost and coverage are ours and made up — put yours in
The same build against two wage levels. The line is not slightly different. It is a different decision.

Six jobs, run through the formula

These are the six a small business is most often sold. The verdicts below are reasoned from the formula on my assumed numbers, not measured across businesses. Yours may differ, and the section after this tells you when.

  1. Keying invoices and statements. High volume, fully specifiable, mistakes are expensive and come back. Clears itonce volume is real — and note it clears on the cost of errors more than on the hours.
  2. Appointment reminders and confirmations. Enormous volume, trivially specifiable, and it does not save labour so much as recover revenue that was walking out. Clears it comfortably, and it is the one nobody gets excited about.
  3. Stock counting. The counting is not the hard part. Deciding what a discrepancy means is, and that is a person. Hire the person.
  4. First-reply customer support. Half your questions are not really questions, they are somebody who is annoyed. Answering the easy half fast makes the hard half angrier, because they now know a fast reply was available. Hire the person.
  5. Payroll and attendance.Low volume, once a month, highly exception-driven, and every exception is somebody’s pay. Hire the person. Buy them a decent tool.
  6. Sales follow-up. The follow-up is not the value. The judgement about who to follow up and what to say is, and it is the part that cannot be specified. Hire the person.

Four out of six. And I want to be clear that this costs us money to write, because four of those six are things we are perfectly capable of building and would be paid to build.

What actually decides it, and it is not the hours

Notice what the two survivors have in common, because it is not “the boring ones.”

Neither of them wins on labour cost. Reminders win because a no-show is lost revenue and the automation recovers it at a volume no person could cover. Invoice keying wins because a wrong invoice costs far more than the minutes it took to type it. At Indian wages, hours are cheap and mistakes are not, so the automation that pays is the one that prevents an expensive event, not the one that saves time.

That is the whole local adjustment, in one sentence, and it is why imported payback maths misleads here. Where labour is expensive, saving hours is the win. Where labour is not, it usually is not.

When the four flip

Nothing above is a law. Three things move it, and if any of them is true for you, redo the sum:

  • Volume ten times higher. f × S is per person, but volume decides how many people. At enough scale the fourth and sixth change sides.
  • The mistake is very expensive. If one wrong stock figure costs a week of production, counting stops being about counting.
  • You cannot hire. If the role is genuinely unfillable where you are, the comparison is not automation against a person. It is automation against the work not happening, and that is a different sum with a different answer.

Run the four numbers before your next conversation with anybody selling this, including us. If the payback is past about twelve months, the honest answer is usually a person and a better tool for them to use.

How this paper was made

This paper is a formula and six worked applications of it. Every salary, build cost and running cost in it is one we chose, stated as ours where it appears, and meant to be replaced with the reader’s own payroll and volumes.

The task-based framework is Autor’s and is cited. The historical account of the Luddites is drawn from Thompson, also cited; the point taken from it is about the accuracy of the objection, not about machine-breaking.

We have not measured error rates, payback periods or outcomes across a population of Indian businesses. The conclusion that two of these six roles clear break-even is reasoning from the arithmetic under our assumptions, and it is labelled as such on the card above. If your volume is ten times ours, it changes.

This paper argues against buying four things we could sell you. That is deliberate and it is not softened.

On the date at the top of this page. This paper is dated 3 August 2026 because that is its slot in the series. The writing and the working were done on 26 August 2026, when the series was compiled and released together. We would rather say that here than have you find it in the page history.

References

  1. Autor, D. H. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives, 29(3), 3–30. Automation displaces tasks rather than whole jobs, and complements the tasks it cannot do.
  2. Thompson, E. P. (1963). The Making of the English Working Class. Victor Gollancz. The account this paper draws on for what the Luddites were actually objecting to.