Automation index
How much of a Watchmaker’s job can AI already do?
A diagnosis and a spare come earlier. Opening the movement so it keeps time again do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Watchmaker
22%
AI can already do 22% of this job.
#376 / 633
View rankingWatchmaker
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 |
|---|---|---|---|
Diagnose, quote and explain to the client.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Open, strip, clean and oil the movement.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Spares, rate adjustment and calibration.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Cases, straps, water resistance and polish.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The counter, commissions and pieces that do not come back.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Times, real spares and a watch that keeps time.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- repair watches
- open movements
- oil calibres
- adjust rate
- change straps
- water-resistance test
- diagnose watches
- polish cases
Sources for this job· O*NET 51-9071.00· ESCO/ISCO 7311
IS WORK OVER?
Last-mile manager
26%
#211 / 633
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