Automation index
How much of a Community health worker’s job can AI already do?
A workshop and a leaflet come earlier. Reaching the person who never walks into the clinic do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Community health worker
24%
AI can already do 24% of this job.
#256 / 623
View rankingCommunity health worker
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 |
|---|---|---|---|
Health map, workshops and the calendar.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Street, doorway and the neighbour who does not come.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Vaccines, screening and referring to the clinic.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Data, report and the health table.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The rumour, the distrust and not moralising.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they come, and not inflating workshop numbers.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
- health workshops
- health map
- door-to-door
- refer to clinic
- screening
- health table
- community vaccination
- health distrust
Sources for this job· O*NET 21-1094.00· ESCO/ISCO 3253
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