Automation index
How much of a SAP specialist’s job can AI already do?
A customising and a report come earlier. Payroll coming out on the 30th does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
SAP specialist
25%
AI can already do 25% of this job.
#224 / 623
View rankingSAP specialist
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 |
|---|---|---|---|
Customising, specs and module tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Integrations, IDocs and interface faults.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Key user, training and resistance.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Go-lives and windows.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Documentation, authorisations and audit.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Not leaving a company unable to invoice.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 25% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Customising, specs and module tests
- Integrations, IDocs and interface faults
- Key user, training and resistance
- Go-lives and windows
- Documentation, authorisations and audit
- Not leaving a company unable to invoice
- especialista sap
- consultor sap
- erp specialist
Sources for this job· O*NET 15-1211.00· ESCO/ISCO 2511
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