Automation index
How much of a Social educator’s job can AI already do?
A report and a plan come earlier. Being with someone on the street and not dropping them does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Social educator
20%
AI can already do 20% of this job.
#459 / 643
View rankingSocial educator
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 |
|---|---|---|---|
Reports, individual plans and paperwork.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Accompany on the street, in flats and in the centre.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 10% | +2.2 |
Mediate families, resources and crises.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Coordinate services, courts and mental health.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Shifts, team and supervision.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not abandoning the person nobody wants.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 20% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Reports, individual plans and paperwork
- Mediate families, resources and crises
- Shifts, team and supervision
- Not abandoning the person nobody wants
- educador social
- educadora social
- social educator
Sources for this job· O*NET 21-1021.00· ESCO/ISCO 2635
IS WORK OVER?
Last-mile manager
26%
#216 / 643
View rankingLast-mile manager
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 |
|---|---|---|---|
Zones, capacity and route cuts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
KPIs, first attempt and incidents.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
The courier, the lobby and the one who will not open.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Peaks, rain and hiring too many or too few.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The angry customer and not dressing delivered.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Cover the peak, and not leaving the neighbourhood orphaned.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
- delivery zones
- first attempt
- delivery KPIs
- last-mile peaks
- lobbies
- delivery incidents
- courier capacity
- cut routes
Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324