IS WORK OVER?

Automation index

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

A firing curve comes earlier. Glazing without losing the batch in the firing do not.

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

Task comparison

Ceramicist

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
Body, mould and the curve.
Estimate

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

16%32%+5.1
Glaze, apply and the one that runs.
Estimate

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

22%8%+1.8
Kiln, atmosphere and the batch that sticks.
Estimate

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

16%22%+3.5
Run, the order and the one that does not match.
Estimate

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

16%28%+4.5
The gallery, the deadline and not opening the kiln early.
Estimate

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

16%18%+2.9
Not losing the batch, and signing the curve.
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

  • firing curves
  • bodies
  • ceramic moulds
  • glazes
  • atmosphere
  • runs
  • runs of glaze
  • the firing

Sources for this job· O*NET 51-9195.00· ESCO/ISCO 7314

Last-mile manager

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
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
Total100%26%

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

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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