As payroll teams face increasing pressure to process high volumes of data accurately and on time during tax season, artificial intelligence (AI) is gaining traction as a potential productivity tool. But industry experts stress that AI’s role in payroll must remain limited, transparent, and firmly overseen by humans.
“AI can support payroll teams throughout tax season when it serves as support for assisting with the preparation of large volumes of data, not as the main decision maker,” said Rob Lowe, Associate Director of Digital and AI Services at alliant, who manages daily operations for digital and AI services.
Lowe’s cautionary approach reflects a broader regulatory and industry consensus: while AI can improve operational efficiency, payroll remains a high‑risk compliance function where accountability cannot be delegated to automated systems.
Where AI Can Safely Support Payroll Teams
Lowe said AI is best suited for payroll tasks that are repetitive, time‑consuming, and operational in nature—particularly during peak filing periods.
“AI can safely help streamline high‑volume, repetitive tasks,” he said. “In this case, there still needs to be human oversight to verify files before moving forward.”
That dual‑review model is critical in payroll environments, where hundreds of records may cross desks daily. “This way, there are two sets of eyes on hundreds of materials crossing desks each day, with the final call coming from the human, not the machine,” Lowe added.
Federal agencies are adopting similar principles in their own AI governance frameworks. The IRS, for example, released a comprehensive AI governance policy in February 2026 that emphasizes transparency, oversight, and risk mitigation in the use of AI across tax administration functions.
Where AI Should Not Be Used—Even as an Assistive Tool
Despite growing interest in AI‑driven compliance solutions, Lowe draws clear boundaries around what the technology should never do in payroll settings.
“AI should never be used to make compliance decisions or to handle confidential client financial data,” he said. “Additionally, AI should not be used to direct or transfer funds, especially without human consent or approval.”
Payroll errors, Lowe noted, can quickly escalate beyond internal issues. “Even the smallest of errors from AI reliance can domino into a larger issue—impacting audits or employees being paid incorrectly,” he said, adding that these mistakes often lead to “satisfaction conflicts across both internal and external teams.”
Regulators have reinforced that responsibility for outcomes remains with the employer or service provider. Federal Trade Commission guidance stresses that organizations deploying automated systems remain fully accountable for data security, accuracy, and consumer harm, regardless of whether AI is involved.
Minimum Guardrails Before Peak Payroll Deadlines
Before rolling out AI tools during tax season, Lowe said payroll leaders must invest in both policy development and employee education.
“Ahead of introducing and interacting with any AI assistive services during tax seasons, guardrails need to be in place to both protect and educate employees and teams looking to work with AI,” he said.
Human oversight, he added, is non‑negotiable. “Human‑in‑the‑loop review/approvals are key for any compliance‑related assistance, as well as clear boundaries of when and where AI can be used, versus where it cannot.”
Lowe warned that moving too quickly can backfire. “The biggest mistake I see is teams integrating AI faster than controls are defined and employees are educated,” he said. “If employees don’t know the answers or exactly where to find them, teams enter a gray zone of risk that impacts data, results, and time.”
These concerns align with the National Institute of Standards and Technology’s Artificial Intelligence Risk Management Framework, which emphasizes governance, documentation, and lifecycle risk management as AI use scales.
Handling Sensitive Payroll Data in an AI Environment
Payroll teams routinely manage very important employee information, including employee Social Security numbers, wages, direct‑deposit information, and garnishment records. Lowe said this makes caution essential when AI enters the workflow.
“Payroll professionals handle some of the most sensitive data across entire organizations, so it needs to be handled with care,” he said.
Access controls matter, but so does user behavior. “Employees should never copy and paste raw data directly into an AI‑powered tool, especially if this is not public data elsewhere on the internet,” Lowe said.
He also urged organizations to scrutinize vendors closely. “If a vendor or tool cannot clearly explain how data is secured and protected, teams should find an alternate option,” he said, “keeping security a number one priority.”
What ‘Audit‑Ready’ AI Use Looks Like in Payroll
Transparency is another cornerstone of responsible AI use in payroll. Lowe said any AI‑assisted workflow must be fully traceable.
“An audit‑ready workflow shows every step of the way where AI has been utilized,” he said. “It is clear where and when it was used, what it created, what human reviewed and approved it, as well as any changes that were made.”
Each step should be documented. “Every step should be traceable via paper trail or data logs,” Lowe said, “so that both internal and external teams are protected.
The U.S. Government Accountability Office has emphasized similar documentation and inventory requirements as organizations expand AI use in financial and compliance‑driven environments.
Evaluating ‘AI‑Powered’ Payroll Vendors
With AI‑centric payroll tools multiplying, Lowe cautioned firms against relying on marketing claims alone.
“The number of AI‑centric services is steadily expanding, creating a rapidly evolving landscape of tools and providers,” he said. “Organizations must take a comprehensive and methodical approach when evaluating potential partners and vendors.”
That due diligence, he added, should include a close review of how sensitive data is “collected, processed, stored, and potentially shared,” as well as whether a vendor’s governance practices align with regulatory obligations and internal risk standards.
AI, Phishing, and Payroll Fraud Risks
Tax season consistently brings heightened fraud risk, and experts caution that those threats do not disappear once the April 15 individual filing deadline passes—particularly for payroll and employer systems that remain active year‑round.
“As AI continued to infiltrate this tax season, phishing attacks are increasingly more convincing and personalized,” said Lowe. He noted that attackers often exploit periods when payroll and tax teams are under pressure to move quickly.
That warning mirrors the Internal Revenue Service’s annual “Dirty Dozen” tax scam campaign, which continues to flag phishing and impersonation schemes as some of the most persistent threats facing taxpayers, businesses, and tax professionals. In releasing its 2026 Dirty Dozen list, the IRS reiterated that while many scams peak during filing season, they occur throughout the year, with fraudsters frequently targeting employer payroll systems and W‑2 data.
The IRS has repeatedly stressed that scammers rely on urgency, familiarity, and routine business processes that make payroll and HR functions especially attractive targets even after individual tax returns are filed. Just because April 15 has passed for individual filers does not mean employers or payroll departments can let their guard down.
To counter these evolving threats, Lowe emphasized the importance of layered defenses within payroll operations. “Teams must stay vigilant in keeping employee training as up to date and comprehensive against the latest attacks,” he said. He also pointed to practical controls such as multi‑step authentication and mandatory human review for unusual requests or changes.
“Teams should always operate on the side of caution, assuming that any inbound request could be altered,” Lowe added. “Better to properly vet and be safe than sorry.”
Outlook
As payroll departments continue to experiment with AI, Lowe’s message is clear: technology can augment payroll work, but it cannot replace human judgment or accountability.
For payroll professionals, the challenge is not whether to use AI—but how to use it responsibly, transparently, and within well‑defined boundaries that protect employees, employers, and the integrity of the payroll process.
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