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
IS WORK OVER?
Makeup artist
17%
AI can already do 17% of this job.
#601 / 643
View rankingMakeup 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.
| Task | Share | AI | Points |
|---|---|---|---|
Moodboards, lists and quotes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 38% | +6.1 |
Bookings, consents and social.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 28% | +3.9 |
Make up, hair and retouch on set.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 6% | +1.4 |
Difficult skin, allergies and sweat.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 10% | +1.6 |
Talent, director and the clock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
Kit, hygiene and travel.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 16% | +2.2 |
| Total | 100% | 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
IS WORK OVER?
Prompt engineer
34%
#21 / 643
View rankingPrompt engineer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512