Artificial intelligence (AI) is becoming more common in the workplace and it’s easy to see why. It can quickly summarize information and help with everyday tasks. In fact, many employers are actively encouraging employees to improve efficiency by using AI tools. However, a concerning trend is emerging: employers and HR professionals are increasingly turning to general-purpose large language model (LLM) tools, such as ChatGPT and Microsoft Copilot, for critical payroll and compliance guidance.
While these tools can summarize information at impressive speed, the National Payroll Institute is observing a rise in requests from its members to verify AI-generated answers. While AI can provide a useful starting point, incorrect or incomplete information may still result in costly and avoidable errors if the technology is relied on too heavily without professional review.
Payroll is not a collection of abstract facts. It is a discipline governed by a complex web of federal and provincial legislation that changes constantly. When businesses treat AI as a substitute for qualified professional judgment, they expose themselves to financial and legal risks.
“Compliance in payroll is not just about ‘knowing the rules,’” explains Giovanni Stea, PLP, Senior Manager, Year End Program, ADP Canada. “It’s about interpreting legislation, applying nuanced exceptions, understanding jurisdictional differences, making defensible decisions and bearing legal responsibility.”
The Illusion Of Accuracy
The biggest risk of using general-purpose LLM tools for payroll questions is how convincing they sound. These tools provide clear, confident, well-organized answers to compliance questions, making them seem like expert advice. But this can be misleading, especially for someone without strong knowledge of payroll.
Unlike a certified payroll professional, a general-purpose LLM tool model does not necessarily “understand” legislation. It predicts text based on patterns in its training data, which may include outdated information, forum discussions or the laws of different countries. This leads to “hallucinations”: responses that appear accurate and convincing but are actually incorrect or fabricated.
For a business owner or manager using this information to make payroll decisions, the consequences can be serious, including incorrect employee pay, compliance issues, penalties, time-consuming corrections, loss of employee trust and morale, and reputational damage.
For example, a general-purpose LLM tool might incorrectly state that the “Last day for which paid” in Block 11 of an employee’s Record of Employment is simply the last physical day worked, which is true in many cases. However, per the Record of Employment guide from Service Canada, the actual last day for reporting purposes is the last day the employee receives insurable earnings, such as the final paid vacation day, a paid sick day or the last day of salary continuance.
Common Risks In Canadian Payroll
The Canadian Payroll Institute has identified several recurring types of error where AI-generated advice falls short.
1. Complexities of Multi-Jurisdictional Compliance
One of the most frequent mistakes involves providing guidance on employment standards that span multiple provinces. A business operating in several provinces might ask a general-purpose LLM tool to summarize overtime rules. The response may appear comprehensive but it often fails to account for critical nuances.
For example, overtime calculation methods are not uniform. Some provinces require calculations based on hours worked in excess of a daily threshold, others use a weekly threshold and some use a combination of both.
2. Outdated or Incomplete Legislation
General-purpose LLM models are trained on data that may not be current. If a business uses this flawed data to set up its payroll system, the error is compounded with every payroll run, creating a liability that must be corrected, often at the employer’s expense.
3. Absence of Contextual Judgment
Payroll compliance is rarely a simple matter of looking up a rule. It often requires interpreting how a regulation applies to a specific situation.
For example, calculating statutory holiday pay can involve different methods depending on whether the employee worked, was on leave or had variable earnings during the qualifying period.
The Indispensable Role Of Payroll Professionals
The risks outlined represent a direct threat to an organization’s financial health and legal standing. The CRA and provincial authorities hold employers accountable for compliance, regardless of whether an error was the result of human oversight or misplaced trust in technology. The CRA will not offer leniency on the basis that incorrect advice was generated by an AI tool or any third-party source. In fact, the CRA’s own GenAI chatbot includes a disclaimer that it does not offer authoritative or binding tax advice.
AI cannot replace the human oversight needed to interpret ambiguous legislation or make judgments about risk and liability. Organizations that recognize this distinction are far better positioned to protect themselves from risk, maintain compliance and uphold employee trust. Ultimately, the most effective approach is not choosing between technology and human expertise, but ensuring they are used together appropriately, with qualified professionals making the final, informed decisions that keep payroll accurate, compliant and fair.
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This article contains excerpts from Dialogue Magazine, which is a benefit exclusive to National Payroll Institute Members. Find out more about NPI membership here.
Photo by Solen Feyissa on Unsplash