Automation index
How much of a Education specialist’s job can AI already do?
A curriculum design and a report come earlier. Actually changing a school does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Education specialist
25%
AI can already do 25% of this job.
#248 / 623
View rankingEducation specialist
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 schemes, rubrics and assessments.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Reports, diagnoses and school plans.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Train staff and accompany teams.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Observe class and feed back with care.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Families, inspectorate and EU projects.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Not selling pedagogical fashion without a classroom.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 25% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design schemes, rubrics and assessments
- Reports, diagnoses and school plans
- Train staff and accompany teams
- Observe class and feed back with care
- Families, inspectorate and EU projects
- pedagogo
- pedagoga
- education specialist
Sources for this job· O*NET 25-9031.00· ESCO/ISCO 2351
IS WORK OVER?
Mobile developer
28%
#92 / 623
View rankingMobile developer
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 |
|---|---|---|---|
Screens, API and offline state.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Store review, crashlytics and ANRs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Real device, the notch and fragmented Android.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
CI, tests and the week's release.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Product, the redesign and not breaking what people use.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not crash, and not ignoring the one-star.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- build apps
- ship to stores
- crashlytics
- offline state
- ANRs
- mobile tests
- fragmented Android
- store review
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514