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.
#502 / 633
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?
Mobile developer
28%
#92 / 633
View rankingMobile 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.
| Task | Share | AI | Points |
|---|---|---|---|
Screens, API and offline state.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Store review, crashlytics and ANRs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Real device, the notch and fragmented Android.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
CI, tests and the week's release.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Product, the redesign and not breaking what people use.EstimateNo 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.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 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