IS WORK OVER?

Automation index

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

A joint set-out comes earlier. No ugly cut and holding the water do not.

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

Task comparison

Wall tiler

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, level and the tile format.
Estimate

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

16%32%+5.1
Adhesive, set and the tray fall.
Estimate

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

22%8%+1.8
Cut, drill and the tile that splits.
Estimate

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

16%22%+3.5
Grout, seal and the bath junction.
Estimate

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

16%28%+4.5
The client, the model change and the stock that is late.
Estimate

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

16%18%+2.9
No ugly cut, and no leak.
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

  • tile walls
  • set out joints
  • bed tiles
  • tray fall
  • seal junctions
  • cut tiles
  • drill tile
  • grout

Sources for this job· O*NET 47-2044.00· ESCO/ISCO 7122

Last-mile manager

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
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
Total100%26%

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

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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