11 practical uses for AI in payroll processing

1. Identify discrepancies

Many employees' hours and pay remain fairly constant from one pay period to the next. AI can alert employees, managers and the payroll team if significant deviations occur during the payroll period.

This capability enables payroll staff to resolve errors quickly, before payroll processing begins, avoiding bigger problems later.

In newer payroll systems, this often takes the form of anomaly detection, where AI highlights patterns that fall outside historical norms rather than relying only on fixed thresholds.

2. Highlight issues in real time

AI can also identify issues as users enter and submit them, reducing the number of errors that reach payroll staff. For example, AI can immediately flag an employee entering more than 80 hours worked over a two-week period.

The technology can detect missing or unusual entries in real time and route them for review, while payroll systems enforce holds based on predefined approval rules.

3. Process draft payroll runs

A payroll system with AI can automatically run draft payroll runs as data is entered and approved. Doing so enables the software to catch potential issues early and alert the payroll team before the final payroll run is processed.

Doing draft payroll runs saves time later when payroll staff is trying to get payroll processed and finalized before the deadline.

Some platforms now pair draft runs with explanations that show which inputs or changes triggered adjustments, helping payroll staff validate results more quickly.

4. Improve compliance

One of the biggest challenges of running payroll is making sure each employee's pay complies with the regulations for each jurisdiction. International companies, in particular, must ensure their payroll meets each country's, state's or province's tax laws and work-hour regulations.

AI can automatically detect compliance issues, helping payroll departments continue to meet regulatory requirements. 

While AI can help identify potential compliance issues as rules change, it does not replace legal interpretation or local expertise. Compliance still depends on keeping rules current, documenting decisions, and maintaining audit-ready records.

5. Answer employee questions

Employees, managers and payroll team members might all encounter issues or have questions while using payroll software and its associated systems. AI can answer user questions and recommend next steps if applicable.

These capabilities can save time for payroll team members, as they have less questions to answer from employees outside the payroll department.

In practice, these tools are most effective when they handle routine questions and escalate complex or sensitive issues to payroll staff.

6. Automate reminders

Two steps in payroll that payroll staff must often complete manually are reminding employees to complete their timesheets and reminding managers to approve timesheets and time-off requests.

AI in payroll software can automatically send out reminders and escalate noncompliance when necessary, saving payroll staff time.

Many systems now adjust reminders dynamically based on past behavior, escalating only when delays become habitual.

7. Confirm employee core data

Processing payroll requires information from each employee, such as their address, hourly rate or salary, and government ID, such as a Social Security number.

AI can validate that required fields are present, notice inconsistencies and recommend updates, while changes to sensitive information still require human review and approval.

AI can validate that required fields are present, notice inconsistencies, and recommend updates, while changes to sensitive information still require human review and approval.

8. Automatically update benefits

Employees can experience changes in benefits, including when they join a company or when a life event triggers a benefits switch. AI can automatically adjust employees' benefits costs in the payroll system.

This capability can also be helpful when a company updates its benefits options, which often occurs yearly.

As with payroll data, benefit changes are typically applied within defined rulesets and reviewed to ensure accuracy.

9. Assist with calculations

Payroll staff must complete many calculations during a payroll run, with potential calculations including a terminated employee's final pay, employees' overtime pay, vacation days taken versus earned, and company-specific items, such as investments or loan repayments.

Payroll systems can handle many of the underlying calculations, but teams still need to review the results before finalizing a run. This tends to matter most in edge cases, where the math works but the outcome doesn't quite line up with real-world circumstances.

10. Detect fraud

Unauthorized changes to timesheets, benefits or investments can occur, or suspicious patterns might emerge, such as recurring expenses from an employee.

Payroll data isn't static, and over time, certain changes can stand out for the wrong reasons. That might look like overtime increasing sharply without a clear explanation, bank account details being updated more often than expected, or approvals following an unusual pattern. AI can continually review data for unapproved changes or concerning patterns and alert users if the tech identifies any issues.

11. Support audits and explain payroll decisions

Payroll teams are increasingly expected to explain how pay was calculated, approved and corrected. AI can help by maintaining audit trails, summarizing changes between payroll runs, and showing which inputs or rules influenced outcomes.

When payroll runs are questioned -- by finance, managers, auditors or employees -- teams usually need to walk through what changed and why. That often means comparing one run to the last, checking which data was updated, and confirming where approvals happened.

Payroll systems that make it easier to trace those changes can save time during reviews and reduce back-and-forth when questions arise. Being able to see what moved, what stayed the same, and where exceptions were handled makes payroll decisions easier to explain after the fact. As payroll systems continue to evolve, the most effective use of AI will focus on making payroll operations more predictable, auditable and manageable, rather than fully autonomous.

Editor's note: This article was updated in January 2026 to improve clarity, flow and the overall reader experience.

Eric St-Jean is an independent consultant with a particular focus on HR technology, project management and Microsoft Excel training and automation. He writes about numerous business and technology areas.