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 / 623
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?
Data engineer
31%
#36 / 623
View rankingData 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 pipelines, models and orchestration.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 50% | +12 |
Write SQL, Spark and data tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Incidents, quality and lineage in production.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to analysts and negotiate data contracts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Cloud cost, permissions and PII.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Decide architecture and technical debt.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design pipelines, models and orchestration
- Write SQL, Spark and data tests
- Cloud cost, permissions and PII
- Decide architecture and technical debt
- ingeniero de datos
- data engineer
- etl
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511