Skip to content
man bot

Plant and machine operators, and assemblers · code 8322

Car, taxi and van drivers

Car, taxi and van drivers drive and tend motorcars and vans to transport passengers, mail or goods. Tasks include - (a) driving and tending passenger vans, cars or taxis; (b) driving and tending cars, vans or small trucks to deliver mail or goods; (c) assisting passengers with handling of luggage; (d) collecting fares, payments for deliveries, or documents certifying deliveries; (e) operating telecommunications equipment to report location and availability, and following directions of control centre; (f) determining most appropriate route; (g) assisting physically challenged passengers; (h) operating equipment to facilitate the loading and unloading of physically challenged passengers. Examples of the occupations classified here: - Ambulance driver - Car driver - Parking valet - Taxi driver - Van driver Some related occupations classified elsewhere: - Driver (motorized rickshaw) - 8321 - Bus driver - 8331 - Heavy truck driver - 8332 - Pedal vehicle driver - 9331 - Rickshaw puller - 9331 - Animal-drawn vehicle driver - 9332

The mildest of the ILO’s four “exposed” groups. It ranks 220 of 427 for holding up against AI.

Also known as

  • patient transport services driver
  • private chauffeur
  • armoured car driver
  • parking valet
  • delivery driver
  • taxi driver
  • hearse driver

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

72.4
Holds up
against AI Exposed: Gradient 1

AI could take on 27.6 of 100, on average
so it holds up at 100 − 27.6 = 72.4

That's the whole sum, and you can check it against the ILO's study.

68.9
How hands-on
out of 100

From O*NET, averaged across 6 US jobs

37.9
How fiddly
and cramped

finger skill 36.8 · hand skill 38.8 · cramped spaces 38.2 · averaged

Kind of hands-on work · hands-on 50+ · fiddly under 39.4 Hands-on, less fiddly work

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

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 0.7-work-setting measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

This number is probably too high

This score only looks at AI tools like chatbots. It doesn't look at robots at all — and this job rates 68.9 out of 100 for how hands-on it is, which is exactly where robots come in.

Have a look at the tasks below and judge for yourself. The ILO scored them low because a chatbot can't do them. Whether a machine with hands could is a different question, and we can't answer it yet.

The tasks behind the score

The score is the average of these. A job is really a bundle of tasks, and an average can hide how uneven that bundle is.

The task AI could do most of scores 73.5, while the average is 27.6. A big gap means some of this job is wide open to AI and some of it barely at all. That's quite different from a job where everything sits somewhere in the middle, even when the averages match.

  1. 73.5

    Determining most appropriate route

    Medium
  2. 48.5

    Operating telecommunications equipment to report location and availability, and follow directions of control centre

    Low
  3. 35

    Collecting fares, payments for deliveries, or documents certifying deliveries

    Low
  4. 17.3

    Driving and tending passenger, vans, cars or taxis

    Very Low
  5. 16.5

    Driving and tending cars, vans or small trucks to deliver mail or goods

    Very Low
  6. 12.3

    Assisting physically challenged passengers

    Very Low
  7. 10

    Assisting passengers with handling of luggage

    Very Low
  8. 8

    Operating equipment to facilitate the loading and unloading of physically challenged passengers.

    Very Low

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

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.7-work-setting

Helped, or replaced?

The score above can't tell a tool that makes you faster from one that does the task instead of you. Jobs and Skills Australia looked at those two things separately, and this is their result, matched to this job.

4 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.

AI helps you
57.3
AI does it for you
38

Helping wins by 19.3 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 4111, 5612, 7311, 7321

Compared with similar jobs

There are 39 jobs in the “Plant and machine operators, and assemblers” group, averaging 80.3. This one is below that.