Automation index
How much of a Archaeologist’s job can AI already do?
A report and a sheet come earlier. Digging and not breaking the context do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Archaeologist
22%
AI can already do 22% of this job.
#320 / 633
View rankingArchaeologist
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 |
|---|---|---|---|
Sheets, drawing and the intervention report.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Excavate, sieve and record units.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 12% | +2.4 |
Authorities, developer and site deadlines.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Lab, dating and publication.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Store, conservation and outreach.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not losing a context by going too fast.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Excavate, sieve and record units
- Authorities, developer and site deadlines
- Lab, dating and publication
- Store, conservation and outreach
- Not losing a context by going too fast
- arqueologo
- archaeologist
Sources for this job· O*NET 19-3091.00· ESCO/ISCO 2632
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