Automation index
How much of a Data protection officer’s job can AI already do?
A processing record and a clause come earlier. Calling an incident and answering the regulator do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Data protection officer
29%
AI can already do 29% of this job.
#58 / 623
View rankingData protection officer
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 |
|---|---|---|---|
Processing records, clauses and DPIAs.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Policies, processor contracts and transfers.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Data-subject rights, internal queries and training.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Incidents, notification and the call to the regulator.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Vendors, cookies and new processing.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Independence, board report and liability.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- data protection
- apply GDPR
- run DPIAs
- handle subject rights
- notify breaches
- draft clauses
- processor contracts
- answer the regulator
Sources for this job· O*NET 13-1041.00· ESCO/ISCO 2422
IS WORK OVER?
Data architect
28%
#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