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 / 633
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?
Statistician
26%
#201 / 633
View rankingStatistician
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 |
|---|---|---|---|
Model, clean and visualise.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 48% | +9.6 |
Design sample, experiment and biases.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Client, questions and not overfitting.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Reproducibility, code and documentation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Publication, review and data ethics.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not selling a p-value that does not hold.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Model, clean and visualise
- Design sample, experiment and biases
- Client, questions and not overfitting
- Reproducibility, code and documentation
- Publication, review and data ethics
- Not selling a p-value that does not hold
- estadistico
- statistician
Sources for this job· O*NET 15-2041.00· ESCO/ISCO 2120