IS WORK OVER?

Automation index

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

A doneness chart comes earlier. Marking on the grill and serving it at the point do not.

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

Task comparison

Grill cook

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
Cut, ageing and the requested doneness.
Estimate

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

16%32%+5.1
Grill, mark and the fire that dies.
Estimate

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

22%8%+1.8
Rest, plate and the one that goes cold.
Estimate

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

16%22%+3.5
List, shrink and the expensive cut.
Estimate

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

16%28%+4.5
The full room and not working too far ahead.
Estimate

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

16%18%+2.9
At the point, and not drying the cut.
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

  • mark on the grill
  • doneness
  • ageing
  • rest
  • plate
  • cuts
  • grill shrink
  • the fire

Sources for this job· O*NET 35-2014.00· ESCO/ISCO 5120

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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