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Professionals · code 2353

Other language teachers

Other language teachers teach non-native languages to adults and children who are learning a language for reasons of migration, to fulfil employment requirements or opportunities, to facilitate participation in educational programmes delivered in a foreign language, or for personal enrichment. They work outside the mainstream primary, secondary and higher education systems, or in support of students and teachers within those systems. Tasks include - (a) assessing the level of ability and the extent of language difficulties of students, and establishing students’ needs and learning goals; (b) planning, preparing and delivering lessons and workshops for groups and individuals, with content and rate of progression adapted to students’ abilities and needs; (c) designing and producing teaching materials and adapting existing materials; (d) assessing students’ progress; (e) assisting students in classroom settings where subjects are taught in a language other than the students’ native language; (f) providing assistance to other teachers by designing special teaching programmes for students still learning the main language of instruction; (g) assigning and correcting work, and preparing and grading exams; (h) assessing, recording and reporting on students’ progress. Examples of the occupations classified here: - Intensive language teacher - Migrant education teacher - Practical language teacher - Second language teacher Some related occupations classified elsewhere: - University lecturer - 2310 - Vocational education teacher - 2320 - Secondary school teacher - 2330 - Primary school teacher - 2341

A few tasks are affected, but the heart of the job isn't. It ranks 266 of 427 for holding up against AI.

Also known as

  • language school teacher
  • sign language teacher

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

66.1
Holds up
against AI Minimal Exposure

AI could take on 33.9 of 100, on average
so it holds up at 100 − 33.9 = 66.1

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

21.5
How hands-on
out of 100

From O*NET, averaged across 4 US jobs

12.4
How fiddly
and cramped

finger skill 21.8 · hand skill 10.4 · cramped spaces 5.2 · averaged

Kind of hands-on work · hands-on under 50 Less than half hands-on

Less than half of this job is hands-on. Robots still matter, but for a smaller part of the work, so we don't sort it any further.

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 21.5 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, but for work this far from the physical that matters less.

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 51.5, while the average is 33.9. 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. 51.5

    Assigning and correcting work, and preparing and grading exams

    Medium
  2. 50

    Designing and producing teaching materials and adapting existing materials

    Medium
  3. 33.5

    Assessing, recording and reporting on students’ progress.

    Low
  4. 32

    Assessing students' progress

    Low
  5. 28.8

    Assessing the level of ability and the extent of language difficulties of students, and establishing students' needs and learning goals

    Low
  6. 26.5

    Providing assistance to other teachers by designing special teaching programmes for students still learning the main language of instruction

    Low
  7. 25.5

    Planning, preparing and delivering lessons and workshops for groups and individuals with content and rate of progression adapted to students’ abilities and needs

    Low
  8. 23.5

    Assisting students in classroom settings where subjects are taught in a language other than the students’ native language

    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.

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

AI helps you
73.5
AI does it for you
53.5

Helping wins by 20 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 2492, 2493

Compared with similar jobs

There are 92 jobs in the “Professionals” group, averaging 61.3. This one is above that.