Elementary occupations · code 9621
Messengers, package deliverers and luggage porters
Messengers, package deliverers and luggage porters carry and deliver messages, packages and other items on foot, within an establishment or between establishments, to households and elsewhere, or carry luggage, especially at hotels, stations and airports. Tasks include - (a) delivering messages, packages and other items within an establishment or between establishments or elsewhere; (b) delivering various goods to and from enterprises, shops, households and other places; (c) carrying and delivering luggage at hotels, stations, airports, and elsewhere; (d) receiving and marking baggage by completing and attaching claim checks; (e) planning and following the most efficient route; (f) sorting items to be delivered according to the delivery route. Examples of the occupations classified here: - Hotel porter - Luggage porter - Messenger - Leaflet deliverer - Newspaper deliverer Some related occupations classified elsewhere: - Mail carrier - 4412 - Postman/woman - 4412
The mildest of the ILO’s four “exposed” groups. It ranks 299 of 427 for holding up against AI.
Also known as
- hotel porter
- doorman/doorwoman
Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.
against AI Exposed: Gradient 1
AI could take on 37 of 100, on average
so it holds up at 100 − 37 = 63
That's the whole sum, and you can check it against the ILO's study.
out of 100
From O*NET, averaged across 2 US jobs
and cramped
finger skill 33.9 · hand skill 37.5 · cramped spaces 18.2 · 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
What this number leaves out This job rates 67.6 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, and for work like this robots are the bigger question.
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 70, while the average is 37. 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.
- 70
Planning and following the most efficient route
Medium - 42.5
Sorting items to be delivered according to the delivery route.
Low - 40.5
Receiving and marking baggage by completing and attaching claim checks
Low - 25
Delivering various goods to and from enterprises, shops, households and other places
Low - 24
Delivering messages, packages and other items within an establishment or between establishments, or elsewhere
Very Low - 20
Carrying and delivering luggage at hotels, stations, airports, and elsewhere
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 0.7-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.
3 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.
- AI helps you
- 47.7
- AI does it for you
- 29.7
Helping wins by 18 points.
estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 4319, 5612, 8999
Compared with similar jobs
There are 33 jobs in the “Elementary occupations” group, averaging 85.7. This one is below that.
- Vehicle cleaners 91.1
- Water and firewood collectors 91.1
- Crop farm labourers 90.9
- Garbage and recycling collectors 90.8
- Civil engineering labourers 90.7
- Forestry labourers 90.6
- Building construction labourers 90.6
- Sweepers and related labourers 90.6
- Other cleaning workers 89.8
- Mining and quarrying labourers 89.1
- Odd job persons 89
- Window cleaners 88.9
- Fishery and aquaculture labourers 88.9
- Mixed crop and livestock farm laboure… 88.7
- Garden and horticultural labourers 88.4
- Cleaners and helpers in offices, hote… 88.1
- Livestock farm labourers 88.1
- Manufacturing labourers not elsewhere… 88
- Kitchen helpers 87
- Drivers of animal-drawn vehicles and … 86.8
- Freight handlers 85.9
- Domestic cleaners and helpers 85.7
- Hand launderers and pressers 85.6
- Street and related service workers 82.1
- Refuse sorters 81.9
- Fast food preparers 81.7
- Hand packers 80.2
- Shelf fillers 79.5