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
IS WORK OVER?
Window installer
19%
AI can already do 19% of this job.
#512 / 643
View rankingWindow 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.
| Task | Share | AI | Points |
|---|---|---|---|
Measure openings, subframe and the order.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Set, plumb and the missing packer.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Foam, seal and the sweating lintel.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Fittings, adjust and the sash that rubs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The lived-in house and not leaving the room freezing.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
That it closes, and not trapping the lintel.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 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
IS WORK OVER?
Agile coach
24%
#262 / 643
View rankingAgile 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.
| Task | Share | AI | Points |
|---|---|---|---|
Boards, metrics and the cadence design.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The real retro and the elephant in the room.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Train, unblock and the manager who will not let go.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Scale, dependencies and fake agile.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Conflict, power and not selling extra frameworks.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they stop faking it, and not inflating velocity.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 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