Automation index
How much of a NGO programme officer’s job can AI already do?
A report and an indicator come earlier. The project existing outside the slide deck do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
NGO programme officer
26%
AI can already do 26% of this job.
#213 / 633
View rankingNGO programme officer
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, indicators and the report.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Justify, invoices and the donor.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Field or neighbourhood and what does not fit the frame.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Partners, meetings and coordination.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The surprise, the cut and redoing the timetable.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That it works, and not inflating the indicator.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- design projects
- justify to donors
- indicators
- activity report
- coordinate partners
- timetable
- project invoices
- neighbourhood work
Sources for this job· O*NET 21-1093.00· ESCO/ISCO 2635
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