Automation index
How much of a Payroll clerk’s job can AI already do?
A payroll engine comes earlier. Paying right without leaving anyone at zero do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Payroll clerk
27%
AI can already do 27% of this job.
#183 / 623
View rankingPayroll 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 |
|---|---|---|---|
Starters, variables and the engine.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Incidents, the missed day and overtime.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Social security, tax and the month’s return.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Query, the payslip and the one who does not get it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The close, the rush and not paying twice.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Pay right, and not leaving anyone at zero.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
- payroll starters
- variables
- income tax
- social security
- payslips
- overtime
- payroll close
- incidents
Sources for this job· O*NET 43-3051.00· ESCO/ISCO 4313
IS WORK OVER?
Logistics analyst
28%
#79 / 623
View rankingLogistics analyst
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 |
|---|---|---|---|
Costs, OTIF and the dashboard.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Simulate network, warehouses and the what-if.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Ops, dirty data and going down to the dock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Report, the board and the cut that hurts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The haulier, the contract and not breaking the service.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
A real saving, and not dressing OTIF.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
- logistics costs
- OTIF
- simulate network
- what-if
- dirty data
- haulage contracts
- dashboards
- network cuts
Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421