Explainable AI and Transparency in AI-Based HR Systems: The Roles of Trust and Technology Readiness

The increasing use of artificial intelligence in human resource management raises critical challenges related to employee trust and acceptance of AI based HR systems. This study examines the effects of explainable AI and algorithm transparency on employee acceptance, with perceived trust as a mediating variable and technology readiness as a moderating variable. A quantitative research design was employed by collecting survey data from employees and HR practitioners who have experience using AI based HR systems. The data were analyzed using Partial Least Squares Structural Equation Modeling. The results indicate that explainable AI and algorithm transparency have significant positive effects on perceived trust. Perceived trust, in turn, significantly influences employee acceptance of AI based HR systems. The mediation analysis confirms that perceived trust plays a significant mediating role in linking explainable AI and algorithm transparency to employee acceptance. In addition, technology readiness has a significant direct effect on employee acceptance. However, the interaction effect between perceived trust and technology readiness is not statistically significant, indicating that technology readiness does not function as a true moderating variable but rather as an independent predictor. From a sustainability perspective, these findings support the development of fair, ethical, and inclusive digital work practices aligned with SDG 8 and 9. Overall, this study provides theoretical and practical insights for organizations seeking to implement AI based HR systems in a transparent, trustworthy, and human centered manner.