Transforming the Payroll Industry With Generative AI

The payroll industry is on the brink of a major transformation, fueled by the adoption of generative artificial intelligence, an industry expert said. This innovative technology offers remarkable benefits, including reduced operating costs, improved payroll accuracy, faster processing times, enhanced employee experience, increased compliance efficiency, and better decision-making capabilities, she added.

“AI is not new, but it is developing, and its advancements are revolutionizing the payroll industry,” said Tracy Bowles, global payroll advisory practice leader at Hackett Group. Bowles spoke at PayrollOrg’s Capital Summit in Arlington, Virginia.

Intelligent Automation Framework
There are various ways to utilize AI beyond traditional methods, according to Bowles. Generative AI mimics human intelligence, while predictive automation augments human intelligence, Bowles said.

Other AI tools, such as conversational assistants and intelligent data capture, aim to mirror human interaction and interpretation, further streamlining various payroll functions, she continued. Task automation imitates human actions, whereas intelligent automation simulates human work management, she added.

Payroll professionals can use AI in different ways to streamline the payroll process. Robotic process automation, for instance, allows for the automation of repetitive tasks, drastically improving accuracy and control while speeding up payroll processes, Bowles said. This technology ensures that payroll runs smoothly without the need for constant human oversight, she added.

Intelligent data capture systems play a vital role in compliance by accurately extracting employee data from both digital and analog sources, she said. This can be particularly beneficial for meeting garnishment compliance requirements, Bowles said.

Conversational assistants like chatbots offer 24/7 support, answering employees’ payroll-related inquiries and significantly enhancing their experience, she continued. “Conversational assistants enhance employee experience with instant, 24/7 support at scale,” Bowles said.

Predictive analytics further empowers payroll departments by reducing payroll errors and forecasting future needs and potential risks, enabling organizations to better plan their cash flow by anticipating total payroll costs, Bowles said.

The integration of agile orchestration can help coordinate various payroll processes and technologies in real time, enhancing workflow efficiency, she added.

Generative AI simplifies the creation of payroll-related content and helps analyze payroll trends, allowing professionals to devote less time to documentation and more to addressing complex payroll issues, Bowles said, highlighting the benefits of generative AI adoption in payroll.

Generative AI Adoption in Payroll
Generative AI is based on large language models, primarily the internet, Bowles said. Generative AI can create new content and understand natural language and context like humans, she added.

While generative AI can extract, classify, summarize, infer, generate, and contextualize data, it still needs the human touch for maximum optimization, she said. “Gen AI operates much like a well-educated yet inexperienced college student, who is full of potential but still learning the ropes,” Bowles said.

Employers can adopt generative AI in three primary ways, she said. Employers can do this through embedded solutions that integrate generative AI uses into existing third-party platforms, domain-specialized AI tools that leverage industry-specific expertise, and native solutions built within organizations to meet specific needs, Bowles explained.

Payroll professionals are increasingly adopting generative AI for structured, unstructured, and interactive works, with chatbots at the forefront, she said. However, generative AI is leading in business objective realization, Bowles said. For instance, generative AI helps payroll professionals automate multistate taxation and validate year-end wage statements, she continued.

As employers are increasingly embracing generative AI in payroll, understanding the risks, limitations, and governance of public generative AI is important, Bowles said. Associated risks and limitations such as accuracy concerns, traceability issues, potential data breaches, and liability exposure must be addressed proactively by the adoption of AI-governance policies, she said.

“Payroll professionals should not turn their businesses over to AI but should work alongside it. AI content should be reviewed, monitored, and moderated,” Bowles said. Employers must adopt AI-use policies within their organizations to regulate how employees use public generative AI. These policies will help mitigate the risks associated with generative AI, she added.

Additionally, investing in training and education is vital to equip employees with the knowledge to navigate the complexities of generative AI effectively, she said.

The pace of growth in generative AI applications within payroll is expanding, with significant advancements observed in areas like documentation, service centers, employee communication, analytics, audits, and reporting, Bowles said. Expectations for further expansion in payroll scheduling and fraud detection continue to rise, signaling a new era for the payroll industry, she noted.