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 / 633
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?
Prompt engineer
34%
#21 / 633
View rankingPrompt 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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512