Automation index
How much of a Station master’s job can AI already do?
A train graph comes earlier. Leaving on time without meeting on the same line do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Station master
23%
AI can already do 23% of this job.
#302 / 633
View rankingStation master
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 |
|---|---|---|---|
Graph, orders and the station log.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Platforms, the crossing and the late train.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Staff, shifts and the ticket-office gap.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Incident, passengers and the PA.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Works, closures and leaving nobody on the platform.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they do not meet, and signing the graph.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 23% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- train graph
- orders
- platforms
- ticket office
- PA
- line crossings
- station shifts
- station logs
Sources for this job· O*NET 53-4031.00· ESCO/ISCO 4323
IS WORK OVER?
Prompt engineer
34%
#21 / 633
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