IS WORK OVER?

Automation index

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

A moodboard and a product list come earlier. Odd skin, a live show, and sweat do not.

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

Task comparison

Makeup artist

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
Moodboards, lists and quotes.
Estimate

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

16%38%+6.1
Bookings, consents and social.
Estimate

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

14%28%+3.9
Make up, hair and retouch on set.
Estimate

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

24%6%+1.4
Difficult skin, allergies and sweat.
Estimate

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

16%10%+1.6
Talent, director and the clock.
Estimate

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

16%12%+1.9
Kit, hygiene and travel.
Estimate

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

14%16%+2.2
Total100%17%

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

Skills and activities

  • Moodboards, lists and quotes
  • Bookings, consents and social
  • Make up, hair and retouch on set
  • Difficult skin, allergies and sweat
  • Talent, director and the clock
  • Kit, hygiene and travel
  • maquillador
  • makeup artist
  • maquillaje

Sources for this job· O*NET 39-5091.00· ESCO/ISCO 5142

Train conductor

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
Consist, brakes and the departure sheet.
Estimate

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

16%36%+5.8
Platform, close-up and the one left outside.
Estimate

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

18%12%+2.2
Incidents, Control and the delay.
Estimate

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

16%28%+4.5
Ticket staff, the fare dodger and the clash.
Estimate

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

16%22%+3.5
The line, the points and not leaving early.
Estimate

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

18%18%+3.2
Leave nobody behind, and sign the consist.
Estimate

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

16%12%+1.9
Total100%21%

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

Skills and activities

  • train consist
  • platform close-up
  • departure sheet
  • Control
  • brake check
  • line incidents
  • halts
  • delays

Sources for this job· O*NET 53-4031.00· ESCO/ISCO 8312

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