IS WORK OVER?

Automation index

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

A cutting list comes earlier. A tight close without the glass sweating do not.

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

Task comparison

Aluminium carpenter

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
Measure, cutting list and the profile cut.
Estimate

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

16%36%+5.8
Assemble, squares and the frame in the opening.
Estimate

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

18%12%+2.2
Glass, beads and the one that does not seal.
Estimate

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

16%22%+3.5
Fittings, tilt-and-turn and the fine adjust.
Estimate

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

16%28%+4.5
The dirty site and not scratching the anodising.
Estimate

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

18%18%+3.2
A tight close, and not leaving water in.
Estimate

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

16%12%+1.9
Total100%21%

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

Skills and activities

  • cut profiles
  • assemble frames
  • beads
  • tilt-and-turn
  • seal glass
  • anodising
  • squares
  • measure openings

Sources for this job· O*NET 47-2211.00· ESCO/ISCO 7213

Logistics analyst

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
Costs, OTIF and the dashboard.
Estimate

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

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

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

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

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

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

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

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

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

18%14%+2.5
A real saving, and not dressing OTIF.
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

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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