Automation index
How much of a Warehouse supervisor’s job can AI already do?
A dock dashboard comes earlier. Getting the shift out without mixing the goods do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Warehouse supervisor
24%
AI can already do 24% of this job.
#270 / 633
View rankingWarehouse supervisor
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 |
|---|---|---|---|
Docks, waves and the shift plan.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The team, the peak and the one who cannot keep up.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Stock, shrink and the mystery gap.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Safety, forklifts and the near miss.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The late haulier and not mixing the docks.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Get the shift out, and not mixing the goods.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
- plan docks
- waves
- warehouse shift
- shrink
- forklifts
- near misses
- outbound peaks
- mixed goods
Sources for this job· O*NET 53-1048.00· ESCO/ISCO 1324
IS WORK OVER?
Last-mile manager
26%
#211 / 633
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