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?
Prompt engineer
34%
#21 / 623
View rankingPrompt 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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512