Automation index
How much of a Ticket inspector’s job can AI already do?
A validator comes earlier. Walking the train and dealing with no ticket do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Ticket inspector
22%
AI can already do 22% of this job.
#378 / 633
View rankingTicket inspector
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 |
|---|---|---|---|
Validate, fares and the intervention note.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Aisle, the group and the one who hides.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Fines, data and what you can ask.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Incident, the full train and calling the conductor.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The insult, keeping calm and not making a scene.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Charge fairly, and not skipping a coach.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- validate tickets
- rail fares
- interventions
- on-train fines
- walk coaches
- call the conductor
- passenger data
- full trains
Sources for this job· O*NET 53-4031.00· ESCO/ISCO 5112
IS WORK OVER?
Mobile developer
28%
#92 / 633
View rankingMobile developer
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 |
|---|---|---|---|
Screens, API and offline state.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Store review, crashlytics and ANRs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Real device, the notch and fragmented Android.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
CI, tests and the week's release.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Product, the redesign and not breaking what people use.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not crash, and not ignoring the one-star.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- build apps
- ship to stores
- crashlytics
- offline state
- ANRs
- mobile tests
- fragmented Android
- store review
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514