Automation index
How much of a Language teacher’s job can AI already do?
A drill and a correction come earlier. Getting a shy person talking for an hour does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Language teacher
23%
AI can already do 23% of this job.
#310 / 633
View rankingLanguage teacher
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Prepare lessons, worksheets and corrections.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Class, conversation and group dynamics.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 12% | +2.6 |
Assess speaking, writing and levels.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Platform, homework and follow-up.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Families, schools and official exams.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Not leaving someone mute in a language.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 23% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- teach class
- mark students
- lesson plans
- teach
- Class, conversation and group dynamics
- Assess speaking, writing and levels
- Platform, homework and follow-up
- Families, schools and official exams
- Not leaving someone mute in a language
- profesor de idiomas
Sources for this job· O*NET 25-3011.00· ESCO/ISCO 2353
IS WORK OVER?
Pizza maker
20%
#463 / 633
View rankingPizza maker
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Dough, ferment and the day’s point.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Open, top and the oven at a thousand.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Serve, delivery and the one that arrives cold.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
List, costs and the topping that runs out.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Saturday, the queue and not working too far ahead.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Pull it in time, and not leaving it carbonised.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 20% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- open dough
- bake pizza
- ferment
- top pizzas
- the oven
- pizza delivery
- dough point
- Saturday queue
Sources for this job· O*NET 35-2011.00· ESCO/ISCO 5120