Artificial intelligence and unethical financial practices: Examining the mediating role of environmental; social; and governance (ESG) performance in the Saudi financial sector

This study investigates how the adoption of artificial intelligence (AI) influences unethical financial practices—bribery, corruption, fraud (BCF), and tax avoidance—in the Saudi financial sector, with environmental, social, and governance (ESG) performance as a mediating factor. Employing the causal mediation framework of Imai et al. (2010a, 2010b) and Tingley et al. (2014), the analysis uses generalized linear models (GLMs) for BCF, ordinary least squares (OLS) for tax avoidance, and a 5,000-replication bootstrap procedure to enhance inferential robustness. The results reveal partial mediation: while AI adoption is associated with lower ESG performance, higher ESG scores partially mitigate AI’s positive association with unethical practices. This finding implies that although ESG frameworks are effective in attenuating some of AI’s adverse ethical impacts, they are insufficient alone to prevent misconduct. The findings underscore AI’s dual role as a driver of ethical vulnerabilities in the absence of adequate oversight and a catalyst for improved governance when aligned with strong ESG principles. The study extends agency and stakeholder theories by illustrating how ESG serves simultaneously as a governance mechanism to reduce information asymmetry and as a legitimacy instrument to reinforce stakeholder trust in an AI-driven financial ecosystem.