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?
Prompt engineer
34%
#21 / 633
View rankingPrompt 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 prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512