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Plant and machine operators, and assemblers · code 8143

Paper products machine operators

Paper products machine operators monitor and operate machines which produce boxes, envelopes, bags and other goods from paper, paperboard, cardboard and similar materials. Tasks include - (a) operating and monitoring machines which glue paper to cardboard, cut it to the required length or cut and crease cardboard or paperboard to form box blanks; (b) operating and monitoring pressing machines which form drinking cups or other containers from paper, paperboard or cardboard; (c) operating and monitoring machines which cut, fold and glue paper to make envelopes and paper bags, or which form bags from other similar material. Examples of the occupations classified here: - Machine operator (cardboard products) - Machine operator (envelope and paper bag production) - Machine operator (paper box production) - Paper products machine operator - Papier maché moulder

None of this job's tasks scored high enough to count. It ranks 117 of 427 for holding up against AI.

Also known as

  • corrugator operator
  • tissue paper perforating and rewinding operator
  • absorbent pad machine operator
  • paper cutter operator
  • envelope maker
  • paperboard products assembler
  • paper bag machine operator

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

81.9
Holds up
against AI Not Exposed

AI could take on 18.1 of 100, on average
so it holds up at 100 − 18.1 = 81.9

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

74.7
How hands-on
out of 100

From O*NET, averaged across 2 US jobs

46.2
How fiddly
and cramped

finger skill 43.8 · hand skill 42.9 · cramped spaces 51.8 · 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 74.7 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 20, while the average is 18.1. 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. 20

    Operating and monitoring machines which cut, fold and glue paper to make envelopes and paper bags, or which form bags from other similar material.

    Very Low
  2. 18

    Operating and monitoring machines which glue paper to cardboard, cut it to the required length or cut and crease cardboard or paperboard to form box blanks

    Very Low
  3. 16.3

    Operating and monitoring pressing machines which form drinking cups or other containers from paper, paperboard or cardboard

    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 this one closely, so this is about as reliable as it gets here.

AI helps you
50
AI does it for you
22

Helping wins by 28 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 7113

Compared with similar jobs

There are 39 jobs in the “Plant and machine operators, and assemblers” group, averaging 80.1. This one is above that.