Artificial intelligence and recruitment effectiveness in Moroccan companies: Analyzing the mediating roles of trust and perceived fairness

Abstract

Artificial intelligence (AI) is gradually transforming recruitment practices by automating application processing and enhancing the fit between candidates and job positions. However, its effects on recruitment effectiveness do not appear to be systematic and may depend on intermediate mechanisms, particularly trust in AI and perceived fairness of algorithmic decisions. Yet, research examining these two mechanisms jointly remains limited, particularly in the African or Maghreb context. To contribute to this literature, the present study draws on the tripartite ethical framework proposed by Mori et al. (2025) and uses data collected from 160 recruitment professionals working in Moroccan firms, selected through convenience sampling between June and August 2026. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The model explains 79% of the variance in recruitment effectiveness. Trust exerts a complementary partial mediating effect (indirect effect = 0.222; p < 0.001), whereas perceived fairness has no significant direct effect. A sequential specification, introduced post hoc for exploratory purposes, reveals an indirect effect of perceived fairness through trust (0.110; p < 0.001), suggesting that the justice dimension may precede the rights dimension.

JEL Classification: M51, O33

Paper type: Empirical Research