Automation index
How much of a Teaching assistant’s job can AI already do?
A worksheet and a support note come earlier. Sitting with the one who is stuck does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Teaching assistant
20%
AI can already do 20% of this job.
#451 / 643
View rankingTeaching assistant
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 |
|---|---|---|---|
Prepare materials and adaptations.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Support in class, playground and dining hall.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 10% | +2.2 |
Accompany SEN and small mediation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Notes to the teacher and incident log.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Stock, copies and classroom order.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not labelling and not leaving a child alone.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
- design interfaces
- prototypes
- figma
- Prepare materials and adaptations
- Accompany SEN and small mediation
- Notes to the teacher and incident log
- Stock, copies and classroom order
- auxiliar docente
- teaching assistant
Sources for this job· O*NET 25-9042.00· ESCO/ISCO 5312
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