IS WORK OVER?

Automation index

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

A hive log comes earlier. Checking without angering them and taking honey do not.

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

Task comparison

Beekeeper

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
Check, queen and the hive log.
Estimate

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

16%32%+5.1
Honey, supers and the smoker.
Estimate

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

18%12%+2.2
Varroa, treatments and not losing the stand.
Estimate

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

16%28%+4.5
Moving hives, bloom and the move.
Estimate

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

16%22%+3.5
The neighbour, the sting and the field permit.
Estimate

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

18%18%+3.2
Take honey, and not leaving them without stores.
Estimate

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

16%14%+2.2
Total100%21%

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

Skills and activities

  • check hives
  • supers
  • varroa
  • moving hives
  • smoker
  • queen
  • bloom
  • the stand

Sources for this job· O*NET 45-2092.00· ESCO/ISCO 6123

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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