Automation index
How much of a Hairdresser’s job can AI already do?
A moodboard and a booking assemble themselves. Cutting, colouring, and sending the client out happy is the job.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Hairdresser
14%
AI can already do 14% of this job.
#639 / 643
View rankingHairdresser
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 |
|---|---|---|---|
Diary, client cards and salon social posts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Advise cut and colour from references.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 22% | +3.1 |
Cut, style and finish in the chair.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 6% | +1.4 |
Colour, highlights and treatments.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 8% | +1.4 |
Hygiene, sterilisation and till.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 10% | +1.4 |
Care, retention and handling complaints.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 14% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- cut hair
- colour hair
- haircut
- barbering
- Diary, client cards and salon social posts
- Advise cut and colour from references
- Cut, style and finish in the chair
- Colour, highlights and treatments
- Hygiene, sterilisation and till
- Care, retention and handling complaints
Sources for this job· O*NET 39-5012.00· ESCO/ISCO 5141
IS WORK OVER?
Last-mile manager
26%
#216 / 643
View rankingLast-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.
| Task | Share | AI | Points |
|---|---|---|---|
Zones, capacity and route cuts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
KPIs, first attempt and incidents.EstimateNo 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.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Peaks, rain and hiring too many or too few.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The angry customer and not dressing delivered.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Cover the peak, and not leaving the neighbourhood orphaned.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 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