IS WORK OVER?

Automation index

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

A prompt book comes earlier. Calling the cue so the show goes up do not.

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

Task comparison

Stage 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
Book, cues and the day’s plan.
Estimate

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

16%40%+6.4
Show, the delay and the one who is not there.
Estimate

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

18%14%+2.5
Rehearsals, changes and updating the book.
Estimate

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

16%28%+4.5
Crews, the clash and not missing the cue.
Estimate

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

16%22%+3.5
Opening, nerves and not bringing the curtain early.
Estimate

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

18%18%+3.2
That the show goes up, and the cue on time.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • prompt book
  • cues
  • show plan
  • rehearsals
  • crews
  • opening night
  • curtain
  • rehearsal changes

Sources for this job· O*NET 27-2012.00· ESCO/ISCO 3435

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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