IS WORK OVER?

Automation index

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

A key tag comes earlier. Not marking the car and having it ready when they come out do not.

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

Task comparison

Valet

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
Tag, keys and the bay map.
Estimate

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

16%32%+5.1
Drive someone else’s, the tight car park and not marking it.
Estimate

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

22%8%+1.8
The client already out and the car still downstairs.
Estimate

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

16%22%+3.5
Insurance, the knock and who pays.
Estimate

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

16%28%+4.5
The event, the rain and not losing a key.
Estimate

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

16%18%+2.9
No mark, and the car on time.
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

  • keep keys
  • park others’ cars
  • bay map
  • not mark
  • valet events
  • knock insurance
  • tight car park
  • return on time

Sources for this job· O*NET 53-6021.00· ESCO/ISCO 8322

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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