IS WORK OVER?

Automation index

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

A model and a map come earlier. Saying whether a village should evacuate does not.

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

Task comparison

Meteorologist

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
Models, maps and a first forecast.
Estimate

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

18%48%+8.6
Observation, sondes and satellite.
Estimate

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

16%28%+4.5
Warnings, civil protection and media.
Estimate

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

16%22%+3.5
Shift, uncertainty and not over-scaring.
Estimate

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

16%18%+2.9
Verification, archives and research.
Estimate

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

18%16%+2.9
Not sitting on a warning that saves someone.
Estimate

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

16%14%+2.2
Total100%25%

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

Skills and activities

  • Models, maps and a first forecast
  • Observation, sondes and satellite
  • Warnings, civil protection and media
  • Shift, uncertainty and not over-scaring
  • Verification, archives and research
  • meteorologo

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

Logistics analyst

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
Costs, OTIF and the dashboard.
Estimate

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

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

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

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

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

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

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

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

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

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

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

16%12%+1.9
Total100%28%

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

Skills and activities

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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