IS WORK OVER?

Automation index

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

A video and a mark come earlier. The body eight shows, and not breaking, do not.

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

Task comparison

Dancer

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
Learn, mark and memorise.
Estimate

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

16%28%+4.5
Rehearse and perform.
Estimate

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

24%6%+1.4
Body, physio and rest.
Estimate

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

16%12%+1.9
Casting, agents and life between jobs.
Estimate

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

16%22%+3.5
Company, ego and tour.
Estimate

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

14%18%+2.5
Not dancing injured because you stayed quiet.
Estimate

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

14%14%+2
Total100%16%

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

Skills and activities

  • Learn, mark and memorise
  • Rehearse and perform
  • Body, physio and rest
  • Casting, agents and life between jobs
  • Company, ego and tour
  • bailarin
  • bailarina
  • dancer

Sources for this job· O*NET 27-2031.00· ESCO/ISCO 2653

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

Analyse my job

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