Automation index
How much of a Greengrocer’s job can AI already do?
A wholesale order comes earlier. Setting the stall without selling the gone piece do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Greengrocer
22%
AI can already do 22% of this job.
#335 / 633
View rankingGreengrocer
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 |
|---|---|---|---|
Wholesale, season and what is at its point.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Stall, replenish and the piece that softens.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Customer, advice and the one who cannot ripen it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Shrink, cold and closing the day.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The market, the rain and not leaving the stall alone.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
At its point, and not selling what is gone.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
- set the stall
- fruit season
- replenish fruit
- shrink
- ripen
- the market
- wholesale
- advise the customer
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