An Analysis of Machine Learning in Enhancing Human Resource Management Processes

Abstract

The integration of machine learning (ML) into human resource management (HRM) processes has sparked significant interest due to its potential to fundamentally transform organisational practices. This paper investigates the obstacles and prospects associated with machine learning in human resource management operations. Machine learning algorithms can enhance and expedite the applicant screening process, fostering diversity and mitigating bias. Predictive analytics identify high-performing individuals, hence optimising skill development and succession planning. Nonetheless, the integration of machine learning with human resource management is challenging. The ethics, data privacy, and algorithmic bias of automated decision-making require comprehensive scrutiny. Machine learning models must exhibit transparency and integrity to prevent prejudice and uphold public trust.