Building Responsible AI Frameworks for HRM Transformation

The fast adoption of Artificial Intelligence (AI) into Human Resource Management (HRM) offers disruptive possibilities and severe ethical risks at the same time. AI-based applications improve recruitment, performance review, and workforce planning but unless they are properly implemented, they reinforce systemic discrimination, infringe upon employee privacy, and disempower accountability within organizations. The paper is a systematic literature review (SLR) based on thirteen peer-reviewed articles published within 2022-2026, selected by Web of Science (WoS), Scopus, and Q1-Q3 indexed journals, which summarizes the up-to-date picture of knowledge regarding responsible AI-HRM. It finds five thematic clusters, such as (1) responsible AI and ethical governance frameworks; (2) AI transformation of HRM functions; (3) algorithmic bias, fairness, and DEI; (4) bibliometric and systematic mapping studies; and (5) legal and regulatory perspectives. Based on these results, a new six-pillar Responsible AI-HRM Framework (RAIH-F) is suggested, which is mapped on six fundamental HRM functions and implementation mechanisms and quantifiable KPIs. Theoretical contributions, practical implications and a future research agenda are given.