Automation index

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

A fall set-out comes earlier. Leaving a pavement that does not pond do not.

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

Task comparison

IS WORK OVER?

19%

AI can already do 19% of this job.

#560 / 673

Paver

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
Set-out, levels and layer thickness. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Lay, compact and the edge that opens. Estimate No public source provides a precise figure. This is our estimate.	22%	8%	+1.8
Joints, seals and the gully junction. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Plant, mix temperature and the cold day. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Traffic, the closure and not leaving a step. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
No ponding, and not skimping compaction. Estimate No public source provides a precise figure. This is our estimate.	14%	12%	+1.7
Total	100%		19%

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

IS WORK OVER?

22%

#394 / 673

Art teacher

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
Project, the sheet and the kit. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Classroom, the one who will not dare and the one who bins it. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Technique, the mistake and not doing it for them. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Show, the corridor and not hanging only the pretty. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Staff, 'it's a soft subject', and not dropping the bar. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
That they get dirty, and not copying the model. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		22%

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