Automation index
How much of a Data architect’s job can AI already do?
A lake diagram comes earlier. Data that can be used, and does not rot, do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Data architect
28%
AI can already do 28% of this job.
#83 / 623
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
IS WORK OVER?
Order picker
22%
#364 / 623
View rankingOrder picker
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 |
|---|---|---|---|
List, location and the scan.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Aisle, height and the parcel that will not fit.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 10% | +2.2 |
Errors, the short and calling it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Pace, the shift and the pallet that goes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Peaks, Black Friday and not mixing orders.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Hit the SKU, and not leaving a lame pallet.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- picking
- scan locations
- shorts
- build pallets
- warehouse aisles
- order peaks
- SKUs
- voice picking
Sources for this job· O*NET 53-7062.00· ESCO/ISCO 4321