AI empowerment and supervisory board effectiveness: Evidence from an information processing framework

In the context of rapid digitalization and intelligent governance, artificial intelligence (AI) technologies are increasingly embedded in organizational supervision and decision-making processes, fundamentally reshaping how supervisory boards process information and perform monitoring tasks. Drawing on information processing theory, this study develops a moderated mediation model to examine how AI empowerment is associated with supervisory board effectiveness through information transparency, and how this process is contingent upon organizational learning capability. Using survey data collected from 382 supervisory board members and senior managers across multiple industries, this study adopts an organizational-level perspective and employs hierarchical regression and bootstrap analyses to test the proposed hypotheses. The results show that AI empowerment significantly associated with both information transparency and supervisory board effectiveness. Information transparency partially mediates the relationship between AI empowerment and supervisory effectiveness, indicating that AI is positively associated with supervisory performance by optimizing organizational information-processing mechanisms. Moreover, organizational learning capability positively moderates the relationship between AI empowerment and information transparency. However, the moderated mediation effect is not statistically significant, indicating that the indirect effect of AI empowerment on supervisory effectiveness through information transparency remains relatively stable across different levels of organizational learning capability. These findings suggest that organizational learning capability shapes the relationship between AI empowerment and information transparency, but does not significantly alter the overall indirect pathway to supervisory effectiveness.