Automation index

How much of a Category manager’s job can AI already do?

An assortment comes earlier. The category winning without fighting own-label do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

IS WORK OVER?

27%

AI can already do 27% of this job.

#138 / 623

Category manager

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
Assortment, prices and the shelf. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Supplier, the negotiation and the one that will not list. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Promo, the calendar and the one that clashes. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Data, margin and not killing the category. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Own-label, the clash and not hiding it. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That the category wins. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		27%

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

IS WORK OVER?

28%

#109 / 623

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