Automation index
How much of a Book restorer’s job can AI already do?
A paper diagnosis comes earlier. Treating without overworking the copy do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Book restorer
22%
AI can already do 22% of this job.
#377 / 633
View rankingBook restorer
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 |
|---|---|---|---|
Diagnosis, paper and the proposal.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Clean, infill and the one that falls apart.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Sew, bind and the spine.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Box, climate and the store.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The owner, the copy and not leaving it new.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Not overworking the copy, and signing the treatment.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
- paper
- infill losses
- sew sections
- spines
- conservation boxes
- store climate
- book diagnosis
- not overwork
Sources for this job· O*NET 25-4013.00· ESCO/ISCO 2621
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