IS WORK OVER?

Automation index

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

A farm log comes earlier. Treating without taking the neighbour or the river do not.

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

Task comparison

Pesticide applicator

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
Log, product and the dose.
Estimate

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

16%40%+6.4
Apply, drift and the wind that gets up.
Estimate

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

18%12%+2.2
The withholding period and the one who wants in now.
Estimate

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

16%28%+4.5
PPE, the container and the collection point.
Estimate

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

16%22%+3.5
The neighbour, the bees and stopping in time.
Estimate

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

18%18%+3.2
Not taking the river, and signing the treatment.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • farm log
  • pesticide dose
  • drift
  • withholding period
  • PPE
  • empty containers
  • bees
  • field wind

Sources for this job· O*NET 37-3012.00· ESCO/ISCO 6113

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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