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

Agile coach

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
Boards, metrics and the cadence design.
Estimate

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

16%40%+6.4
The real retro and the elephant in the room.
Estimate

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

18%14%+2.5
Train, unblock and the manager who will not let go.
Estimate

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

16%32%+5.1
Scale, dependencies and fake agile.
Estimate

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

16%28%+4.5
Conflict, power and not selling extra frameworks.
Estimate

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

18%18%+3.2
That they stop faking it, and not inflating velocity.
Estimate

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

16%14%+2.2
Total100%24%

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

Skills and activities

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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