Sustainable human resource management: A transformation perspective of human resource management functions through optimised artificial intelligence

Abstract

Human resource management research which links to sustainability and the integration of artificial intelligence (AI) in HR practice has been increased. This paper explores the potential transformation of AI in HRM, revealing the factors that contribute to successful AI adoption and strategies to overcome adoption barriers within organisations. This research aims to verify a model for determining salaries for new employees that is competitive and in line with market standards. This paper also provides practical insights regarding how organisations can effectively analysis the role of HRM and AI to prevent undue evictions of HR professionals. To perform data analysis and processing, this research uses python analysis, with Jupyter notebook software and continues with model testing using regression evaluation model such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and coefficient of determination R2-Score. The four main findings addressed in this study are lack of quality data, bias in data, loss of human aspect, and error and uncertainty. Furthermore, this research provides managerial implications for sustainable HRM practices in overcoming the main problem, namely determining new employee salaries using AI with the best accuracy by oversampling and comparing salaries through job portals to see current market trends.