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.
#290 / 733
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?
Reliability engineer
27%
#175 / 733
View rankingReliability 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 |
|---|---|---|---|
Data, MTBF and the Pareto.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Failure, the cause and not patching twice.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Spare, the critical and not hiding it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
RCM, the plan and the one that is not done.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Production, the rush and not running the tired one.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not drop at three, and not hiding the spare.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- MTBF
- Pareto
- root causes
- critical spares
- RCM
- failures
- maintenance plans
- not patch twice
Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141