THE SOCIO-TECHNICAL IMPACT OF AI IN HRM: THE GENDER PAY GAP IN KAZAKHSTAN

Abstract

This study investigates how Artificial Intelligence (AI) biases in Human Resource Management (HRM) contribute to the persistent 25.7% gender wage gap in Kazakhstan. The research aims to establish how algorithmic systems, often perceived as «objective», codify historical and structural discrimination into mathematical justifications for unequal pay. Utilizing an integrative literature review methodology, the study analyzed 51 peer-reviewed articles to synthesize diverse theoretical and empirical perspectives on AI’s socio-technical impact. The findings identify four themes based on thematic analysis with its critical mechanisms through which bias is automated (historical mirroring, neutrality assumption, the codification of desired salary, the motherhood penalty).  By specifically examining the architectural features of dominant national recruitment platforms HeadHunter.kz  and Enbek.kz , the research results suggest that as Kazakhstan rapidly adopts digital tools under national initiatives, it risks institutionalizing systemic inequality. The study implies an urgent need for local algorithmic audits and regulatory frameworks to ensure that the technological transition promotes social justice rather than automating the existing wage gap.