Automation index
How much of a Development cooperation officer’s job can AI already do?
An agreement and a frame come earlier. Aligning with the southern partner and not imposing the project do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Development cooperation officer
26%
AI can already do 26% of this job.
#212 / 623
View rankingDevelopment cooperation 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 |
|---|---|---|---|
Agreements, alignment and the SDGs on the card.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Follow-up, missions and reports to the agency.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
The local partner, the counterpart and the disagreement.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Budget, currency and what stays in management.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The context that shifts and reworking the approach.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Not imposing, and accounting on both sides.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
- cooperation agreements
- align with SDGs
- agency reports
- southern partners
- monitoring missions
- hard-currency budget
- counterparts
- accountability
Sources for this job· O*NET 19-3094.00· ESCO/ISCO 2635
IS WORK OVER?
Data architect
28%
#83 / 623
View rankingData architect
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 |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.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
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511