IS WORK OVER?

Automation index

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

A stain card comes earlier. Lifting the stain without eating the colour do not.

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

Task comparison

Dry cleaner

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
Card, fibre and pretreatment.
Estimate

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

16%40%+6.4
Machine, solvent and the delicate garment.
Estimate

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

18%14%+2.5
Press, the finish and the one that marks.
Estimate

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

16%28%+4.5
Job, the groom and the one who wants it now.
Estimate

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

16%22%+3.5
The old stain and not promising miracles.
Estimate

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

18%18%+3.2
Lift the stain, and not eating the colour.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • pretreat stains
  • solvents
  • press
  • delicates
  • job cards
  • finish
  • fibres
  • old stains

Sources for this job· O*NET 51-6011.00· ESCO/ISCO 9121

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

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