IS WORK OVER?

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

Paver

Where the time goes

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.

TaskShareAIPoints
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
Total100%19%

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

Skills and activities

  • lay asphalt
  • compact
  • falls
  • pavement joints
  • gullies
  • mix temperature
  • pavement levels
  • seals

Sources for this job· O*NET 47-2071.00· ESCO/ISCO 7112

Cartographer

Where the time goes

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.

TaskShareAIPoints
Sources, OSM, satellite and generalisation.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Symbology, type and visual hierarchy.
Estimate

No public source provides a precise figure. This is our estimate.

16%48%+7.7
Projections, scales and getting the heights right.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Review with the client, the field and the lie in the data.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Print maps, web maps and updates.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Credit, metadata and owning the map.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%31%

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

Skills and activities

  • make maps
  • generalise cartography
  • symbology
  • choose projection
  • visual hierarchy
  • update OSM
  • web maps
  • maps that do not lie

Sources for this job· O*NET 17-1021.00· ESCO/ISCO 2165

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