IS WORK OVER?

Automation index

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

A flight plan comes earlier. Signing the fuel without leaving the aircraft short do not.

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

Task comparison

Flight dispatcher

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
Plan, NOTAM, METAR and the fuel.
Estimate

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

18%52%+9.4
Slot, alternates and weight.
Estimate

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

16%40%+6.4
The crew, the change and the late aircraft.
Estimate

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

16%22%+3.5
MEL, restrictions and the go or no-go.
Estimate

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

16%28%+4.5
The storm, the diversion and recalculating in time.
Estimate

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

18%14%+2.5
Not leaving it short, and signing the release.
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

  • flight plans
  • NOTAM
  • METAR
  • fuel calc
  • slots
  • MEL
  • alternates
  • operational release

Sources for this job· O*NET 53-2022.00· ESCO/ISCO 3154

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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