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

Hotel concierge

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
Bookings, maps and recommendations.
Estimate

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

16%40%+6.4
Desk, bags and difficult guests.
Estimate

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

20%12%+2.4
Restaurants, tickets and transport.
Estimate

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

16%22%+3.5
Logs, shifts and front-desk coordination.
Estimate

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

16%28%+4.5
Neighbourhood, vendors and errands.
Estimate

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

16%16%+2.6
Not leaving a guest stranded at two in the morning.
Estimate

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

16%14%+2.2
Total100%22%

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

Skills and activities

  • Bookings, maps and recommendations
  • Desk, bags and difficult guests
  • Restaurants, tickets and transport
  • Logs, shifts and front-desk coordination
  • Neighbourhood, vendors and errands
  • conserje
  • concierge
  • portero de hotel

Sources for this job· O*NET 43-4081.00· ESCO/ISCO 4224

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