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?

24%

AI can already do 24% of this job.

#270 / 633

Warehouse supervisor

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. Estimate No 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. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Stock, shrink and the mystery gap. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Safety, forklifts and the near miss. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The late haulier and not mixing the docks. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Get the shift out, and not mixing the goods. Estimate No 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

IS WORK OVER?

28%

#109 / 633

BIM modeller

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
Model, families and clash detection. Estimate No public source provides a precise figure. This is our estimate.	18%	52%	+9.4
IFC, BEP and trade coordination. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Site, the one who will not open the model, and the meeting. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Quantities, parameters and the 4D nobody uses. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The last-minute change and not breaking the federated model. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That it can be built, and not over-modelling. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low