IS WORK OVER?

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

Payroll 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.

TaskShareAIPoints
Starters, variables and the engine.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Incidents, the missed day and overtime.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Social security, tax and the month’s return.
Estimate

No 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.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The close, the rush and not paying twice.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Pay right, and not leaving anyone at zero.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%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

Logistics 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.

TaskShareAIPoints
Costs, OTIF and the dashboard.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%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

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