October 2022

5 Ways Artificial Intelligence, Machine Learning Improve Global Payroll Management

AI Feature
By S. Ananda Murali

Artificial intelligence (AI) and machine learning (ML)—a subset of AI—augment the analytical capabilities of enterprises with their ability to analyse both structured and unstructured data to enhance productivity and efficiency.

The workforce often views a new generation of smart machines powered by AI with suspicion and fear. Some may worry that this will replace the human workforce and make some jobs obsolete. But there is a bright side to AI that frees humans from routine tasks, enabling them to take on more value-added tasks. Of course, the changes will require employees to retrain and switch job categories. An October 2020 Forbes article, which cited the World Economic Forum (WEF), reported that AI-driven technology would supplant 85 million jobs currently held by humans by 2025. However, the WEF also anticipates that a tech-driven economy will create 97 million new jobs.

According to a McKinsey estimate, AI has the potential to create business value between $3.5 trillion and $5.8 trillion annually across nine business functions. Data-intensive payroll management is one such function that benefits from the application of AI and ML. AI enhances payroll management by automating manual repetitive processes and efficiently handling data, while eliminating errors. It also helps in faster and more accurate classification of employees during pay calculations and tax deductions. Conversational AI enables query resolution 24/7 and improves productivity and reduces costs. AI helps in efficiently managing constantly changing government regulations, employee incentives and bonuses, and other changes.

Here are five ways AI and ML improve global payroll management:

  1. Data Integration

    Employee data used in payroll processing is distributed across different enterprise applications such as human capital management (HCM), enterprise resource planning (ERP), and sometimes in Excel spreadsheets. The data must be integrated into global payroll applications, verified, and validated before processing. This leads to incomplete and inaccurate data getting populated in the global payroll systems unless manually checked, which also has the potential to create errors.

    Automated systems powered by AI help to clean and validate data through rule-based validation, leading to accurate results. Moreover, AI prevents process re-runs saving time and money, and eliminates manual efforts leading to enhanced efficiency.

  2. Value-Added Work

    The payroll team is responsible for answering employees’ questions and handling incident responses related to payroll issues. Many organizations lack a dedicated employee support team to answer these payroll-related questions, which leads to payroll professionals spending significant time in payroll support attending phone calls and answering emails.

    Traditional chatbots—powered by conversational AI—help payroll professionals to address employee payroll queries. Conversational AI uses Natural Language Processing (NLP) and ML tools to facilitate human-like interactions between computers and humans through automated text and voice-enabled applications. These are commonly referred to as chatbots, which can be programmed to answer routine payroll queries and escalate complex queries to the professionals.

    AI chatbots provide immediate answers to employee queries in a chat window without having employees wait for replies through email, phone calls, or other means. This enables payroll professionals to devote adequate time to their core and value-added work.

  3. Process Optimization

    The automation of payroll tasks enables organizations to collect data that can be utilized to improve processes. The data and information collated by the automated system and chatbots can be used to identify process inefficiencies, which can be enhanced with the help of AI and related technologies.

    The stored data by the chatbot can be used to improvise the conversational agent or chatbot and broaden its scope by automating additional query responses.

  4. Anomaly Detection

    The application of AI and ML in payroll technology has enabled organizations to identify anomalies by using algorithms without any manual intervention. This helps organizations prevent payroll fraud schemes such as ghost employees or timesheet fraud. Furthermore, it prevents unauthorized payments and avoids penalties from regulatory authorities for noncompliance.

  5. Compliance Management

AI automation limits the possibility of human error and improves payroll compliance. The automated alerts and notifications enable payroll teams to diligently meet payroll compliance deadlines and make real-time compliance a reality. 


Future of Payroll Management

Payroll technology will evolve with AI increasingly embedded in the payroll software. The application of AI and ML in payroll management will enhance the role of professionals. The job shift will enable payroll professionals to devote more time to reviewing strategic insights such as employee burnout rates, evolving cyclical patterns, and understanding the implications of new regulations. They will have more time and insights for process improvement and performance management. The automation enabled by AI and ML should be seen as an opportunity by global payroll professionals to develop their skills to add more value to their organizations.

S. Ananda Murali (Sam) joined Ramco Systems in 2013 and is currently the Vice President of Enterprise Solutions at Ramco Systems Corporation in North America. He supports Ramco’s customers and other global organizations in adopting digital transformation using new age intelligent and automated payroll solutions. Murali holds an MBA in engineering and has more than 20 years of IT consulting, solution advisory, and business development experience. He can be reached at [email protected].
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