IS WORK OVER?

Automation index

How much of a Weaver’s job can AI already do?

A weave comes earlier. Warping, weaving without breaking the pick do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Weaver

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.

TaskShareAIPoints
Warp, weave and the width.
Estimate

No public source provides a precise figure. This is our estimate.

16%32%+5.1
Weave, shuttle and the yarn that snaps.
Estimate

No public source provides a precise figure. This is our estimate.

22%8%+1.8
Finish, fringe and the shrink.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Loom, the rhythm and the commissioned piece.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The client, the colour and not changing the warp halfway.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Without breaking the pick, and a clean weave.
Estimate

No public source provides a precise figure. This is our estimate.

14%12%+1.7
Total100%19%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • warp
  • weaves
  • shuttle
  • looms
  • fringe
  • the pick
  • cloth width
  • shrink

Sources for this job· O*NET 51-6062.00· ESCO/ISCO 7318

Data architect

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.

TaskShareAIPoints
Models, lineage and the catalogue.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it gets used, and not letting raw data rot.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • model data
  • lineage
  • data catalogue
  • data contracts
  • pipeline quality
  • retention
  • data lakes
  • privacy

Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511

Analyse my job

Jobs with similar scores

  1. 539Hydrogen technician19%
  2. 540Small-hydro technician19%
  3. 541Surgical technologist19%
  4. 543Occupational therapist19%
  5. 544Tractor driver19%
  6. 545Stagehand19%