Automation index
How much of a Tailor’s job can AI already do?
A pattern comes earlier. Fitting, marking and hanging on the body do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Tailor
19%
AI can already do 19% of this job.
#532 / 633
View rankingTailor
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 |
|---|---|---|---|
Pattern, measures and the fitting.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Cut, tack and the shoulder that will not hang.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Fit, mark and the client who loses weight.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Buttonholes, lining and the hand finish.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The groom, the deadline and not rushing the hem.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Hang on the body, and not leaving a high shoulder.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
- take measures
- patterns
- tack
- buttonholes
- tailor fittings
- linings
- hem
- shoulder
Sources for this job· O*NET 51-6052.00· ESCO/ISCO 7531
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