Digital Human Resource Management for Inclusive and Sustainable Workplaces
TL;DR
The findings indicate that algorithmic systems may reproduce existing inequalities through biased training data, proxy variables, and design assumptions, and the importance of embedding fairness and inclusion into digital HRM governance is emphasized.
Abstract
The integration of artificial intelligence (AI) into human resource management (HRM) creates opportunities for efficiency while raising concerns about algorithmic bias, discrimination, and workplace inequality. This study systematically reviews literature on digital HRM, diversity, equity, and inclusion (DEI), and algorithmic fairness to examine their implications for inclusive and sustainable workplaces. Guided by PRISMA 2020 and informed by PRISMA-S, the review synthesizes conceptual and empirical research on AI-enabled HRM, workplace inclusion, and sustainable human resource practices. The findings indicate that algorithmic systems may reproduce existing inequalities through biased training data, proxy variables, and design assumptions. Although AI can improve recruitment and operational efficiency, fair outcomes require transparency, accountability, human oversight, and continuous evaluation. The review also identifies limited integrated empirical evidence connecting algorithmic fairness, DEI, and sustainable HRM, particularly regarding long-term employee well-being and organizational outcomes. These findings emphasize the importance of embedding fairness and inclusion into digital HRM governance. Future research should prioritize real-world evaluations, intersectional fairness, and longitudinal investigations of employee autonomy and workplace sustainability.