Automation index
How much of a Pizza maker’s job can AI already do?
A dough recipe comes earlier. Opening, baking and pulling it in time do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Pizza maker
20%
AI can already do 20% of this job.
#463 / 633
View rankingPizza maker
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 |
|---|---|---|---|
Dough, ferment and the day’s point.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Open, top and the oven at a thousand.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Serve, delivery and the one that arrives cold.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
List, costs and the topping that runs out.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Saturday, the queue and not working too far ahead.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Pull it in time, and not leaving it carbonised.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 20% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- open dough
- bake pizza
- ferment
- top pizzas
- the oven
- pizza delivery
- dough point
- Saturday queue
Sources for this job· O*NET 35-2011.00· ESCO/ISCO 5120
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