Automation index
How much of a Billing clerk’s job can AI already do?
An ERP comes earlier. Issuing the right invoice without blocking the client do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Billing clerk
27%
AI can already do 27% of this job.
#152 / 623
View rankingBilling clerk
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 |
|---|---|---|---|
Orders, delivery notes and the invoice.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
VAT, withholdings and the one that does not square.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Credit notes, the credit and the client who argues.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Close, the immediate supply and the deadline.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Sales, the extra and not over-billing.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
The right invoice, and not blocking the client.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- delivery notes
- invoices
- VAT
- credit notes
- immediate supply
- billing close
- withholdings
- orders
Sources for this job· O*NET 43-3021.00· ESCO/ISCO 4311
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