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Elementary occupations · code 9332

Drivers of animal-drawn vehicles and machinery

The fares could be taken by app. The horse still needs a driver.

Collecting fares is mostly out of AI's reach. It barely touches the other eight tasks, including harnessing and driving animals and hauling wagons.

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

Drivers of animal-drawn vehicles and machinery drive animal-drawn vehicles to transport passengers or goods, as well as animal-drawn machinery usually in connection with farming. Tasks include - (a) harnessing animals and hitching them to vehicles or machinery; (b) loading or unloading goods, or assisting passengers in getting on or off a vehicle; (c) driving animals in the desired direction with due regard to other traffic and traffic regulations; (d) collecting fares or charges; (e) driving animals to haul wagons in mines or quarries; (f) driving animals hitched to farm or other machinery; (g) driving working elephants; (h) maintaining vehicle or machinery, making minor repairs and installing replacement parts; (i) grooming and feeding animals. Examples of the occupations classified here: - Animal-drawn vehicle driver - Animal train driver - Mahout Some related occupations classified elsewhere: - Jockey - 3421

  • carriage driver

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

87 / 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

50 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 9 tasks for how much of it AI could do. They average 13.2 out of 100, so it holds up at 100 − 13.2 = 86.8.

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?

Drivers of animal-drawn vehicles and machinery 87

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.

  • Taking fares and bookings by app.
  • Scheduling rides and routes.
  • Records for animal welfare checks.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Handling and driving animals safely in traffic.
  • Grooming, feeding and caring for animals.
  • Loading goods and helping passengers.

Both

What's arriving

New work that only exists because the AI does.

  • Tourism bookings online.
  • Stricter welfare rules and inspections.
  • Heritage and events work.

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.

Threat level: Low

20 could do without you

It could take over very little of the work on its own. It could help with 41 of 100.

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 43 out of 100. The higher it is, the longer the robot waits.

65 How
hands-on
43 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, matched to one US job .

finger skill 32.1 · hand skill 46.4 · cramped spaces 51.2 · 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 33, against an average of 13. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 33

    Collecting fares or charges

    Low
  2. 16

    Driving animals in the desired direction with due regard to other traffic and traffic regulations

    Very Low
  3. 15

    Maintaining vehicle or machinery, making minor repairs and installing replacement parts

    Very Low
  4. 14

    Loading or unloading goods, or assisting passengers in getting on or off a vehicle

    Very Low
  5. 14

    Grooming and feeding animals.

    Very Low
  6. 10

    Driving animals hitched to farm or other machinery

    Very Low
  7. 8

    Driving working elephants

    Very Low
  8. 6

    Harnessing animals and hitching them to vehicles or machinery

    Very Low
  9. 5

    Driving animals to haul wagons in mines or quarries

    Very Low

9 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

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
41
AI does it for you
20

Sidekick wins, by 21 points.

How good a match is this?

One Australian job matches this one closely, so this is about as reliable as it gets here.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 8999

So, should carriage and animal drivers be worried?

Short answer: not really. Put the kettle on.

No. The most exposed task is collecting fares, rated Low; everything else, from driving animals to grooming them, rates Very Low. Payment apps may take over the cash; the animals don't need software.

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 →