AI-Based Workforce Optimization in ERP Systems and Its Impact on Labor Cost Efficiency

This study examines the role of AI-integrated ERP systems in optimizing workforce management and improving HR cost efficiency. Today, due to the need for organizations to digitally transform, Enterprise resource planning (ERP) systems are enhanced with tools that can enhance system capabilities such as learning algorithms and predictive analytics capabilities. This paper uses a comparative approach to examine the difference between traditional ERP systems and AI-based models and their impact from the perspective of optimizing HR costs. In this study, the researcher also analyzes the reduction of financial losses caused by incorrect hiring decisions using predictive analytics capabilities to prevent human resource shortages and overstaffing. Labor optimization, as well as increasing the accuracy of cost allocation, and ultimately reducing human resource costs, have been identified through mechanisms resulting from previous empirical and conceptual studies and findings. Furthermore, this study describes the relationship between ERP systems integrated with AI and measurable indicators of labor cost efficiency with a conceptual model. In this conceptual model, the researcher suggests a path that improves workforce planning processes and enhances financial performance through AI in the ERP system. These findings will contribute to the digital transformation in human resource management. And it will give organizations the insight to achieve increased cost efficiency through ERP system integration and AI.