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Plant and machine operators, and assemblers · code 8183

Packing, bottling and labelling machine operators

Packing, bottling and labelling machine operators monitor and operate machines which weigh, pack and label various products or fill different containers with products. Tasks include - (a) operating and monitoring machines that weigh, wrap, seal and pack various products; (b) operating and monitoring machines that fill and seal tubes, bottles, cans, boxes, bags and other containers with products such as food, beverages, paints, oils and lotions; (c) operating and monitoring machines that, by gluing or other methods, label products, packages and various containers. Examples of the occupations classified here: - Bottle filler - Canning machine operator - Labelling machine operator - Packing machine operator - Wrapping machine operator Some related occupations classified elsewhere: - Hand packer - 9321

None of this job's tasks scored high enough to count. It ranks 172 of 427 for holding up against AI.

Also known as

  • cylinder filler
  • footwear finishing and packing operator
  • cigar brander
  • canning and bottling line operator
  • packaging and filling machine operator
  • heat sealing machine operator
  • leather goods packing operator

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

77.7
Holds up
against AI Not Exposed

AI could take on 22.3 of 100, on average
so it holds up at 100 − 22.3 = 77.7

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

62.7
How hands-on
out of 100

From O*NET, matched to one US job

45.8
How fiddly
and cramped

finger skill 48.3 · hand skill 50 · cramped spaces 39 · averaged

Kind of hands-on work · hands-on 50+ · fiddly 39.4+ Hands-on, fiddly work in tight spaces

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.

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 62.7 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 23, while the average is 22.3. 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. 23

    Operating and monitoring machines that, by gluing or other methods, label products, packages and various containers.

    Very Low
  2. 22.3

    Operating and monitoring machines that weigh, wrap, seal and pack various products

    Very Low
  3. 21.5

    Operating and monitoring machines that fill and seal tubes, bottles, cans, boxes, bags and other containers with products such as food, beverages, paints, oils and lotions

    Very Low

3 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.

One Australian job matches, but only partly: not everyone in it does this job. Treat the numbers as a rough guide.

AI helps you
53
AI does it for you
29

Helping wins by 24 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 8321

Compared with similar jobs

There are 39 jobs in the “Plant and machine operators, and assemblers” group, averaging 80.2. This one is below that.