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.

#536 / 643

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?

25%

#235 / 643

Biomedical engineer

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, validate and document clinical devices and software. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Tests, MDR and risk. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Hospital, clinicians and maintenance. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Vendors, quality and traceability. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
User training and post-market watch. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Not putting a half-built prototype in theatre. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		25%

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