Automation index
How much of a Tram driver’s job can AI already do?
Urban ATO comes earlier. Crossing pedestrians without clipping the badly parked car do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Tram driver
19%
AI can already do 19% of this job.
#487 / 633
View rankingTram driver
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 |
|---|---|---|---|
Checks, log and the cab.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Drive, stops and the pedestrian who steps out.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 8% | +1.9 |
Badly parked car, calls and Control.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Timetable, reliefs and rush hour.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The tourist, the bike and not over-hooting.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 18% | +2.5 |
Hit nobody, and make the terminus.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 19% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- drive trams
- urban stops
- pedestrians
- badly parked cars
- Control
- rush hour
- cab checks
- terminus
Sources for this job· O*NET 53-4041.00· ESCO/ISCO 8311
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