IS WORK OVER?

Automation index

How much of a Olive-oil miller’s job can AI already do?

A yield comes earlier. Cold extracting without overheating do not.

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

Task comparison

Olive-oil miller

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
Intake, yield and the mill log.
Estimate

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

16%40%+6.4
Crush, malaxate and the decanter.
Estimate

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

18%12%+2.2
Temperature, time and the fruitiness.
Estimate

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

16%28%+4.5
Cellar, the batch and the one that goes rancid.
Estimate

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

16%22%+3.5
The campaign, the tractor queue and not heating.
Estimate

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

18%18%+3.2
Cold for real, and not painting the yield.
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

  • crush olives
  • malaxation
  • decanter
  • fruitiness
  • the campaign
  • mill yield
  • oil cellar
  • extraction temperature

Sources for this job· O*NET 51-3092.00· ESCO/ISCO 7514

Strength and conditioning coach

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
Load, GPS and the microcycle.
Estimate

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

16%40%+6.4
Gym, the pattern and the one who cheats.
Estimate

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

18%14%+2.5
Rehab, the injured and not rushing the return.
Estimate

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

16%28%+4.5
Report, the manager and the fight over minutes.
Estimate

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

16%22%+3.5
The peak, pre-season and not grinding them.
Estimate

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

18%18%+3.2
Ready, and not broken.
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

  • load
  • training GPS
  • microcycles
  • rehab
  • movement pattern
  • pre-season
  • reports to the manager
  • the gym

Sources for this job· O*NET 29-9091.00· ESCO/ISCO 3423

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