Automation index
How much of a Special-education teacher’s job can AI already do?
An IEP comes earlier. Adapting so they are really in the group do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Special-education teacher
22%
AI can already do 22% of this job.
#349 / 633
View rankingSpecial-education 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 |
|---|---|---|---|
IEP, aims and coordination.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Classroom, support and the one who overflows.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Family, the report and not selling miracles.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Yard, inclusion and the one left alone.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Staff, resources and fighting for the place.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Really in the group, not on paper.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
- IEP
- classroom support
- family reports
- inclusion
- the yard
- resources
- places
- overflow
Sources for this job· O*NET 25-2051.00· ESCO/ISCO 2352
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