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?

27%

AI can already do 27% of this job.

#165 / 623

Textile engineer

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. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Shop, looms and the warp break. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Supplier, cotton and the sustainability card. Estimate No public source provides a precise figure. This is our estimate.	16%	36%	+5.8
Finishes, shrinkage and fastness tests. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The brand, the deadline and the colour that misses. Estimate No 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. Estimate No 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

IS WORK OVER?

26%

#211 / 623

Last-mile manager

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
Zones, capacity and route cuts. Estimate No public source provides a precise figure. This is our estimate.	16%	44%	+7
KPIs, first attempt and incidents. Estimate No public source provides a precise figure. This is our estimate.	16%	36%	+5.8
The courier, the lobby and the one who will not open. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Peaks, rain and hiring too many or too few. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The angry customer and not dressing delivered. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Cover the peak, and not leaving the neighbourhood orphaned. Estimate No 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