Automation index
How much of a Textile engineer’s job can AI already do?
A dye recipe comes earlier. Getting the colour the same over ten thousand metres do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Textile engineer
27%
AI can already do 27% of this job.
#165 / 623
View rankingTextile engineer
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 |
|---|---|---|---|
Recipes, weaves and piece QC.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Shop, looms and the warp break.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Supplier, cotton and the sustainability card.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Finishes, shrinkage and fastness tests.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The brand, the deadline and the colour that misses.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Ten thousand metres the same, and not hiding the bad yardage.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- dye recipes
- weaves
- looms
- colour fastness
- shrinkage
- piece card
- warp
- textile finishes
Sources for this job· O*NET 17-2199.00· ESCO/ISCO 2141
IS WORK OVER?
Climatologist
27%
#140 / 623
View rankingClimatologist
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 |
|---|---|---|---|
Series, homogenise and the gap.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Models, scenarios and the uncertainty.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Report, the headline and not selling the easy one.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Field, the station and the one that moves.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The politician, the figure and not staying quiet.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Attribute, and not selling the headline.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- climate series
- homogenise
- scenarios
- uncertainty
- headlines
- stations
- climate reports
- attribution
Sources for this job· O*NET 19-2021.00· ESCO/ISCO 2112