IS WORK OVER?

Automation index

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

A dough recipe comes earlier. Opening, baking and pulling it in time do not.

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

Task comparison

Pizza maker

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
Dough, ferment and the day’s point.
Estimate

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

16%36%+5.8
Open, top and the oven at a thousand.
Estimate

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

22%8%+1.8
Serve, delivery and the one that arrives cold.
Estimate

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

16%22%+3.5
List, costs and the topping that runs out.
Estimate

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

16%28%+4.5
Saturday, the queue and not working too far ahead.
Estimate

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

16%18%+2.9
Pull it in time, and not leaving it carbonised.
Estimate

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

14%12%+1.7
Total100%20%

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

Skills and activities

  • open dough
  • bake pizza
  • ferment
  • top pizzas
  • the oven
  • pizza delivery
  • dough point
  • Saturday queue

Sources for this job· O*NET 35-2011.00· 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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