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?
Statistician
26%
#201 / 623
View rankingStatistician
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 |
|---|---|---|---|
Model, clean and visualise.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 48% | +9.6 |
Design sample, experiment and biases.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Client, questions and not overfitting.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Reproducibility, code and documentation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Publication, review and data ethics.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not selling a p-value that does not hold.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Model, clean and visualise
- Design sample, experiment and biases
- Client, questions and not overfitting
- Reproducibility, code and documentation
- Publication, review and data ethics
- Not selling a p-value that does not hold
- estadistico
- statistician
Sources for this job· O*NET 15-2041.00· ESCO/ISCO 2120