IS WORK OVER?

Automation index

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

A series comes earlier. Attributing the change without selling the easy headline do not.

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

Task comparison

Climatologist

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
Series, homogenise and the gap.
Estimate

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

18%48%+8.6
Models, scenarios and the uncertainty.
Estimate

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

16%40%+6.4
Report, the headline and not selling the easy one.
Estimate

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

16%22%+3.5
Field, the station and the one that moves.
Estimate

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

16%28%+4.5
The politician, the figure and not staying quiet.
Estimate

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

18%14%+2.5
Attribute, and not selling the headline.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • climate series
  • homogenise
  • scenarios
  • uncertainty
  • headlines
  • stations
  • climate reports
  • attribution

Sources for this job· O*NET 19-2021.00· ESCO/ISCO 2112

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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