Automation index
How much of a Car salesperson’s job can AI already do?
A valuer and stock come earlier. Closing the deal without the car coming back do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Car salesperson
22%
AI can already do 22% of this job.
#399 / 633
View rankingCar salesperson
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 |
|---|---|---|---|
Stock, valuation and the card.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Test drive, objections and the one who will not decide.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Finance, the bank and the one who fails.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Handover, the extra and the one who argues the scratch.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The boss, the margin and not giving the discount away.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Close the deal, and it not coming back.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
- value cars
- test drives
- finance
- handover
- stock
- margin
- scratches
- objections
Sources for this job· O*NET 41-2031.00· ESCO/ISCO 5223
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