Automation index
How much of a Museum educator’s job can AI already do?
A teaching sheet comes earlier. Thirty schoolchildren in front of the work, actually looking, do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Museum educator
24%
AI can already do 24% of this job.
#264 / 623
View rankingMuseum educator
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 |
|---|---|---|---|
Sheets, routes and the teaching kit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
The tour, the group that will not quiet, and the work.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Workshops, families and Sunday at the museum.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
School, bookings and the missing mediator.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Access, the public who do not come in, and adapting.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they actually look, and not reciting the label.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 24% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- school tours
- teaching sheets
- museum workshops
- cultural mediation
- group bookings
- access
- families at the museum
- learning routes
Sources for this job· O*NET 25-4012.00· ESCO/ISCO 2621
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