IS WORK OVER?

Automation index

How much of a Window installer’s job can AI already do?

A measured opening comes earlier. Closing, insulating and not trapping the lintel do not.

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

Task comparison

Window 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
Measure openings, subframe and the order.
Estimate

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

16%32%+5.1
Set, plumb and the missing packer.
Estimate

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

22%8%+1.8
Foam, seal and the sweating lintel.
Estimate

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

16%22%+3.5
Fittings, adjust and the sash that rubs.
Estimate

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

16%28%+4.5
The lived-in house and not leaving the room freezing.
Estimate

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

16%18%+2.9
That it closes, and not trapping the lintel.
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

  • measure openings
  • subframes
  • plumb windows
  • seal lintels
  • adjust sashes
  • foam
  • packers
  • window fittings

Sources for this job· O*NET 47-2121.00· ESCO/ISCO 7125

Mobile developer

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
Screens, API and offline state.
Estimate

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

18%52%+9.4
Store review, crashlytics and ANRs.
Estimate

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

16%40%+6.4
Real device, the notch and fragmented Android.
Estimate

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

16%22%+3.5
CI, tests and the week's release.
Estimate

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

16%28%+4.5
Product, the redesign and not breaking what people use.
Estimate

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

18%14%+2.5
That it does not crash, and not ignoring the one-star.
Estimate

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

16%12%+1.9
Total100%28%

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

Skills and activities

  • build apps
  • ship to stores
  • crashlytics
  • offline state
  • ANRs
  • mobile tests
  • fragmented Android
  • store review

Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514

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