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

Growth manager

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
Analytics, funnels and growth dashboards.
Estimate

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

22%52%+11.4
Copy, creatives and test variants.
Estimate

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

18%48%+8.6
Design experiments and read causality.
Estimate

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

16%22%+3.5
Align product, marketing and sales.
Estimate

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

16%15%+2.4
Ads budget and internal negotiation.
Estimate

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

14%18%+2.5
Decide what dies and what scales.
Estimate

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

14%16%+2.2
Total100%31%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Analytics, funnels and growth dashboards
  • Copy, creatives and test variants
  • Design experiments and read causality
  • Align product, marketing and sales
  • Ads budget and internal negotiation
  • Decide what dies and what scales
  • growth manager
  • growth hacker
  • responsable de growth

Sources for this job· O*NET 13-1161.00· ESCO/ISCO 2431

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