Automation index
How much of a PE teacher’s job can AI already do?
A stock session comes earlier. Getting them actually moving without getting hurt do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
PE teacher
22%
AI can already do 22% of this job.
#367 / 633
View rankingPE 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 |
|---|---|---|---|
Session, aims and the kit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Yard, the group and the one who will not.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Injury, protocol and calling home.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Assess, the report and not giving a 10 for quiet.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Staff, the rain and not leaving them in the corridor.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they move, and not getting hurt.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- PE sessions
- the yard
- injury protocol
- assess PE
- sports kit
- staff meeting
- groups
- the report
Sources for this job· O*NET 25-2031.00· ESCO/ISCO 2330
IS WORK OVER?
Prompt engineer
34%
#21 / 633
View rankingPrompt engineer
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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512