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Elementary occupations · code 9624

Water and firewood collectors

No chatbot carries water. This job is about as far from a screen as work gets.

AI barely touches any of the six tasks, from carrying water from rivers and wells to gathering, bundling and transporting firewood.

What they actually do (and what else they get called)

Water and firewood collectors collect water and firewood and transport them on foot or using hand or animal carts. Tasks include - (a) cutting and collecting wood from forests for sale in market or as fuel or for own consumption; (b) visiting forests or fields to pick pieces of dried wood from the ground and arranging them in heaps; (c) cutting decayed branches and trunks of trees using axes and hand-saws; (d) tying collected wood into small faggots and carrying them or transporting them on a cart to the market for sale or to villages or households for use; (e) drawing water from wells, rivers or ponds, etc. for domestic use; (f) collecting water in leather bags, buckets or other containers from taps, rivers, ponds or wells, and delivering the water to work sites, the houses of clients or to own household for drinking, cleaning of drains or storage in tanks. Examples of the occupations classified here: - Firewood collector - Water collector

91 / 100

Strongly holds up against AI

Most of this job still needs an actual human. AI would mostly be making the tea.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Not Exposed

3 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 6 tasks for how much of it AI could do. They average 8.9 out of 100, so it holds up at 100 − 8.9 = 91.1.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 65 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Water and firewood collectors 91

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • Finding the nearest working water point on a phone map.
  • Checking weather and fire-risk warnings.
  • Arranging sales of wood through messaging apps.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Carrying heavy loads over rough ground.
  • Knowing which wood is dry, safe and allowed to be cut.
  • Judging whether a water source is safe to use.

Both

What's arriving

New work that only exists because the AI does.

  • Maintaining community water pumps and filters.
  • Selling fuel wood through mobile payments.
  • Tree planting and managed woodland schemes.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

– could do without you

We don't have a measure of how much of this job AI could take over.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

65 how hands-on

Most of this job needs hands, a body or turning up. That's robot territory, and nobody measures how far robots have got well enough to give you a number. We won't make one up.

So could a robot do the physical part?

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 46 out of 100. The higher it is, the longer the robot waits.

65 How
hands-on
46 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, averaged across 2 US jobs .

finger skill 42.9 · hand skill 45.6 · cramped spaces 48.6 · averaged · rule: hands-on 50+ · fiddly 39.4+

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 15, against an average of 9. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 15

    Collecting water in leather bags, buckets or other containers from taps, rivers, ponds or wells, and delivering the water to work sites, the houses of clients or to own household for drinking, cleaning of drains or storage in tanks.

    Very Low
  2. 9

    Cutting and collecting wood from forests for sale in market or as fuel or for own consumption

    Very Low
  3. 8

    Drawing water from wells, rivers or ponds, etc. for domestic use

    Very Low
  4. 7

    Cutting decayed branches and trunks of trees using axes and hand-saws

    Very Low
  5. 7

    Tying collected wood into small faggots and carrying them or transporting them on a cart to the market for sale or to village or household for use

    Very Low
  6. 7

    Visiting forests or fields to pick pieces of dried wood from ground and arranging them in heaps

    Very Low

6 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

So, should water and firewood collectors be worried?

Short answer: not really. Put the kettle on.

No. Collecting water and wood is walking, carrying and cutting, and every task rates Very Low. For most people doing it, the bigger changes come from piped water, cleaner cookstoves and roads rather than from AI.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

How are the neighbours doing?

There are 33 jobs in the “Elementary occupations” family, averaging 85. This one is above the family average.

Pit this against any other job →