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# Will AI replace payroll jobs?

Updated October 2026

Payroll clerks score 64 of 100 for AI exposure. The largest share of their task time, 53%, is work AI speeds up while they stay in charge. AI can take over 36% outright, and 11% stays with people.

-   **36%** AI can do it
-   **53%** AI helps
-   **11%** Needs a person

High exposure

Higher than 95% of the 923 occupations we scored.

## Task by task

We graded 21 tasks, listed here from most to least exposed. AI can do 7 of them today, speeds up 12 and leaves 2 to people.

| Task | AI exposure |
| --- | --- |
| Compute wages and deductions, and enter data into computers. Wage and deduction calculations and data entry are highly rule-based. | 80% AI can do it |
| Compile employee time, production, and payroll data from time sheets and other records. Compiling time and payroll data from records is routine digital aggregation. | 75% AI can do it |
| Compile statistical reports, statements, and summaries related to pay and benefits accounts, and submit them to appropriate departments. Summary reports and statistics are generated from payroll data systems. | 75% AI can do it |
| Process and issue employee paychecks and statements of earnings and deductions. Payroll software generates paychecks and statements; clerk mainly reviews output. | 70% AI can do it |
| Record employee information, such as exemptions, transfers, and resignations, to maintain and update payroll records. Updating records for transfers and exits is structured, form-driven data work. | 70% AI can do it |

[See what AI can take on across a finance team](https://www.aigentcy.com/ai-for/finance/)

## How payroll clerks compare

All occupations (923)

Office and administrative support (51)

**Payroll clerks score 64**, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 57 for office and administrative support.

## Pay and outlook in the US

Median pay

$58,260 a year, May 2025

People employed

153,140 in the US, May 2025

Projected change in jobs

\-15.9% from 2024 to 2034

## Skills to build

-   Reconcile gross-to-net pay in ADP Workforce Now
-   Investigate timekeeping exceptions in Kronos Workforce Timekeeper
-   Verify payroll register outputs in Payroll software before release
-   Check tax withholding changes against IRS Publication 15
-   Build variance summaries for pay reports in Microsoft Excel

## Safer roles nearby

5 related occupations with lower scores.

-   [Administrative supervisors55 out of 100](https://www.aigentcy.com/ai-exposure/administrative-supervisors/)
-   [Billing clerks59 out of 100](https://www.aigentcy.com/ai-exposure/billing-clerks/)
-   [Office clerks60 out of 100](https://www.aigentcy.com/ai-exposure/office-clerks/)
-   [Administrative services managers38 out of 100](https://www.aigentcy.com/ai-exposure/administrative-services-managers/)
-   [Credit clerks61 out of 100](https://www.aigentcy.com/ai-exposure/credit-clerks/)

## Questions about payroll clerks and AI

Will payroll jobs be replaced by AI?

Partly. About 6 in 10 working hours for a payroll clerk go to tasks AI can already do, mostly computing wages and deductions and compiling time and payroll data. What stays with people is the review of pay corrections, the check of tax law changes, and the in-person handling of timecards and sign-offs.

Will AI take over payroll jobs?

AI can already do 36% of the task time in payroll and speeds up another 53%. People still do 11% of it. The US has 153,140 payroll clerk jobs, with a projected change of -15.9% from 2024 to 2034.

Which payroll clerk tasks is AI taking over?

Wage and deduction calculations, data entry, and summary reports are the most exposed, each scoring 75 to 80 out of 100. Payroll software calculates deductions, compiles time records into pay runs, and builds statistical reports, so the clerk checks the output the software produces and sends it on to the right department.

Which payroll clerk tasks stay human?

Distributing and collecting timecards scores 15 and recording arrival and departure times scores 20, so both stay with people. Retroactive pay corrections score 55 and need human review because a wrong correction reaches an employee's paycheck. Live training on timekeeping systems also stays with people.

How do payroll clerks stay valuable as AI spreads?

Spend more time on checking outputs, the work that still needs a person to sign off. Reconcile gross-to-net pay in ADP Workforce Now before each pay run, investigate timekeeping exceptions in Kronos Workforce Timekeeper, and check tax changes against IRS Publication 15 before they go live. Build variance summaries in Excel so you can explain pay results to managers.

## Related jobs

-   [Human resources assistants66 out of 100](https://www.aigentcy.com/ai-exposure/human-resources-assistants/)
-   [Bookkeepers67 out of 100](https://www.aigentcy.com/ai-exposure/bookkeepers/)
-   [Eligibility interviewers65 out of 100](https://www.aigentcy.com/ai-exposure/eligibility-interviewers/)
-   [Secretaries66 out of 100](https://www.aigentcy.com/ai-exposure/secretaries/)

## Next steps for payroll clerks

-   ### Check your job
    
    Your job title is a rough guide. Your actual tasks decide your score. Paste your job description or CV and see which of your tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    
-   ### Pay transparency software
    
    The EU Pay Transparency Directive means sharing pay ranges before interviews and reporting pay gaps. Our HR software helps you do both from the pay data you already hold.
    
    [See the HR software](https://www.aigentcy.com/contact/?topic=pay-transparency)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

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-   [**Jobs A to Z**Every job we publish, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/)
-   [**AI exposure by industry**Average scores for 22 occupation groups.](https://www.aigentcy.com/ai-exposure/industries/)
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-   [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/)

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
