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

Home-automation installer

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
Diagram, buses and scene programming.
Estimate

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

16%40%+6.4
Wire, sensors and the switch that does not answer.
Estimate

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

18%14%+2.5
Integrate lights, climate and the client app.
Estimate

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

16%32%+5.1
Train, guest mode and the one who breaks it.
Estimate

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

16%22%+3.5
The lived-in house and not leaving it dark.
Estimate

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

18%18%+3.2
That it obeys, and not needing the cloud for a switch.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • program scenes
  • home buses
  • integrate climate
  • sensors
  • home app
  • switches
  • guest mode
  • wire KNX

Sources for this job· O*NET 47-2111.00· ESCO/ISCO 7411

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