Integration of AI and ML in Payroll Processing System: Automating and Optimising Payroll Management through Intelligent Technologies

Payroll processing is a vital component of organisational management, encompassing salary computation, tax deduction, statutory compliance, and employee compensation management. Traditional payroll systems are largely rule-based and dependent on manual verification, which makes them vulnerable to errors, inefficiencies, and delayed compliance updates. The increasing complexity of payroll regulations and dynamic workforce requirements necessitates the adoption of intelligent and adaptive automation techniques

This paper presents an integrated Artificial Intelligence (AI) and Machine Learning (ML)-based payroll processing system designed to enhance accuracy, efficiency, and regulatory compliance. The proposed framework incorporates supervised learning models for salary and incentive prediction, anomaly detection algorithms for identifying payroll fraud and inconsistencies, and Natural Language Processing (NLP) techniques to automate employee payroll-related queries through an intelligent helpdesk

The system is evaluated using key performance metrics such as accuracy, processing time, and error rate, and is compared with conventional payroll systems. Experimental results indicate that the proposed AI-ML-based system significantly improves payroll accuracy, reduces processing time, and minimises manual intervention. The findings confirm the effectiveness of AI-driven payroll automation and highlight its potential for scalable deployment in modern enterprise environments