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.
#261 / 643
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?
Clinical research associate
27%
#172 / 643
View rankingClinical research associate
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 |
|---|---|---|---|
Protocol, CRF and the monitoring visit.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Source, the gap and the one that does not fit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Adverse event, the deadline and not delaying.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Consent, the signature and the one who did not understand.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The sponsor, the audit and not dressing the figure.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Audit, and not leaving a made-up figure.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
- CRF
- monitoring
- adverse events
- informed consent
- source data
- trial audits
- clinical protocols
- site visits
Sources for this job· O*NET 11-9121.00· ESCO/ISCO 2131