Automation index

How much of a BIM modeller’s job can AI already do?

A model and a clash come earlier. The site being able to build from that model do not.

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

Task comparison

IS WORK OVER?

28%

AI can already do 28% of this job.

#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

IS WORK OVER?

26%

#211 / 623

Last-mile 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
Zones, capacity and route cuts. Estimate No public source provides a precise figure. This is our estimate.	16%	44%	+7
KPIs, first attempt and incidents. Estimate No 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. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Peaks, rain and hiring too many or too few. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The angry customer and not dressing delivered. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Cover the peak, and not leaving the neighbourhood orphaned. Estimate No 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