IS WORK OVER?

Automation index

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

ATO and a log come earlier. Driving a full train and reacting in the tunnel do not.

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

Task comparison

Metro driver

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
Checks, tests and the cab log.
Estimate

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

16%32%+5.1
Drive, stop at platforms and regulate running.
Estimate

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

24%8%+1.9
Incidents, evacuation and talk to Control.
Estimate

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

16%22%+3.5
Timetables, reliefs and the day’s orders.
Estimate

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

16%28%+4.5
Passengers, platforms and announcements.
Estimate

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

14%18%+2.5
Rules, fatigue and liability for the train.
Estimate

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

14%12%+1.7
Total100%19%

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

Skills and activities

  • drive metro trains
  • stop at platforms
  • regulate running
  • evacuate tunnels
  • talk to control
  • cab checks
  • handle incidents
  • drive under ATO

Sources for this job· O*NET 53-4041.00· ESCO/ISCO 8311

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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