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?
Data architect
28%
#83 / 633
View rankingData architect
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 |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511