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Skilled agricultural, forestry and fishery workers · code 6210

Forestry and related workers

Forestry and related workers plan, organize and perform operations to cultivate, conserve and exploit natural and plantation forests. Tasks include - (a) assessing sites for reforestation, selecting seedlings and planting trees using manual planting tools and establishing and caring for forest stands; (b) locating trees to be felled and estimating volume of timber; (c) operating chainsaw and other power saws to thin young forest stands, trim, top and fell trees and saw them into logs; (d) shaping rough wooden products from logs at felling site; (e) stacking logs and loading them in chutes or floating them down rivers; (f) keeping watch to detect forest fires, participating in fire fighting operations, completing fire fighting reports and maintaining fire fighting equipment; (g) controlling weeds and undergrowth in regenerating forest stands using manual tools and chemicals; (h) operating and maintaining a skidder, bulldozer or other prime mover to pull a variety of scarification or site preparation equipment over areas to be regenerated; (i) collecting seed cones, pruning trees, assisting in planting surveys and marking trees for subsequent operations; (j) training and supervising other workers in forestry procedures, including forestry labourers and plant operators. Examples of the occupations classified here: - Charcoal burner - Logger - Logging climber - Skilled forestry worker - Timber cruiser - Tree feller Some related occupations classified elsewhere: - Silviculturist - 2132 - Forestry technician - 3143 - Tree faller operator - 8341 - Forestry labourer - 9215

None of this job's tasks scored high enough to count. It ranks 27 of 427 for holding up against AI.

Also known as

  • forest ranger

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

88.1
Holds up
against AI Not Exposed

AI could take on 11.9 of 100, on average
so it holds up at 100 − 11.9 = 88.1

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

69.7
How hands-on
out of 100

From O*NET, averaged across 5 US jobs

38.2
How fiddly
and cramped

finger skill 38.9 · hand skill 41.8 · cramped spaces 33.9 · 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 69.7 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 21.5, while the average is 11.9. 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. 21.5

    Training and supervising other workers in forestry procedures, including forestry labourers and plant operators.

    Very Low
  2. 16.5

    Keeping watch to detect forest fires, participating in firefighting operations, completing firefighting reports and maintaining firefighting equipment

    Very Low
  3. 16.5

    Operating and maintaining a skidder, bulldozer or other prime mover to pull a variety of scarification or site preparation equipment over areas to be regenerated

    Very Low
  4. 12.5

    Assessing sites for reforestation, selecting seedlings and planting trees using manual planting tools and establishing and caring for forest stands

    Very Low
  5. 12

    Locating trees to be felled and estimating volume of timber

    Very Low
  6. 10.5

    Collecting seed cones, pruning trees, assisting in planting surveys and marking trees for subsequent operations

    Very Low
  7. 7.6

    Controlling weeds and undergrowth in regenerating forest stands using manual tools and chemicals

    Very Low
  8. 7.5

    Shaping rough wooden products from logs at felling site

    Very Low
  9. 7.3

    Operating chainsaw and other power saws to thin young forest stands, trim, top and fell trees and saw them into logs

    Very Low
  10. 7.1

    Stacking logs and loading them in chutes or floating them down rivers

    Very Low

10 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.

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

AI helps you
41
AI does it for you
20

Helping wins by 21 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 3631, 8431, 8999

Compared with similar jobs

There are 18 jobs in the “Skilled agricultural, forestry and fishery workers” group, averaging 83.4. This one is above that.