Abstract
The failure of traditional corporate governance (CG) practices to adequately address the agency problems between shareholders and managers has motivated this novel academic enquiry. This paper investigates the impact of Artificial Intelligence adoption (AIA) on agency costs mitigation and examines the role of AIA in enhancing the effectiveness of traditional CG mechanisms in reducing agency cost. We utilised an international sample comprising 82,323 firm–year observations from 7,537 listed active firms in the US, UK, Canada, Germany, Australia, and China, between the period 2010 to 2023. The main findings indicate that AIA significantly mitigates agency costs. Additionally, AIA reduces information asymmetry, improves executive compensation structure, and enhances the effectiveness of board and audit quality monitoring mechanisms, leading to reduction in agency costs. These findings are robust to battery of analyses including alternative independent, dependent, and control variables, control interactions, lagged variables, change regression, difference–in–difference estimation, panel dynamic GMM and GEE model specifications, instrumental variable methods, propensity score match (PSM), with additional analysis of 1998 dead firms comprising a sample of 14,230 firm–year observations to mitigate survivorship bias. Our heterogeneity analyses further underscore important complementarities between AIA and strong CG practices in addressing agency problems within firms. Overall, this study provides novel empirical evidence that AI holds the promise of mitigating agency problems and reshaping CG practices for more effective agency outcomes, with crucial implications for research and practice in utilizing AI technologies for continuous monitoring, governance and accountability.
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
ARTIFICIAL INTELLIGENCE, CORPORATE GOVERNANCE, AGENCY COST, INFORMATION ASYMMETRY
