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?

27%

AI can already do 27% of this job.

#183 / 633

Payroll clerk

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. 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
Total	100%		27%

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

IS WORK OVER?

24%

#273 / 633

Internist

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
Cross labs, imaging and a differential. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Ward round, examination and decisions. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Explain to family and ceilings of care. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Discharge reports, consults and boards. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Medical on-call and difficult patients. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
Team, residents and not fragmenting the patient. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		24%

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