AI use linked to better board performance through information transparency

A survey of 382 supervisory board members and senior managers across multiple industries found that greater artificial intelligence empowerment in organizational supervision was significantly associated with improved information transparency and more effective supervisory board performance. The study used an information processing framework to examine whether transparency helped explain the link between AI and board effectiveness.

The researchers developed a moderated mediation model to distinguish the direct relationship between AI empowerment and supervisory board effectiveness from the pathway operating through information transparency. They also tested whether organizational learning capability changed the strength of the associations. Analyses at the organizational level used hierarchical regression and bootstrap methods to evaluate the proposed relationships.

Both parts of the model were supported. AI empowerment was positively associated with information transparency, which was itself associated with supervisory board effectiveness. Transparency partially mediated the relationship, meaning that the data were consistent with part of the AI–performance association operating through the organization’s information-processing mechanisms. The findings do not, however, establish that AI caused better governance outcomes.

Organizational learning capability positively moderated the relationship between AI empowerment and information transparency. In other words, the association between AI use and greater transparency was stronger in organizations with greater learning capability. Despite this interaction, the moderated mediation effect was not statistically significant. The indirect effect linking AI empowerment to supervisory board effectiveness through transparency therefore appeared relatively stable across different levels of organizational learning capability.

The study’s scope should be considered alongside its design and sample. The evidence comes from survey responses by supervisory board members and senior managers in several industries, rather than from a controlled experiment or a direct assessment of how AI systems changed specific decisions. Its organizational-level analysis identifies statistical associations among AI empowerment, transparency, learning capability and supervisory effectiveness. The partial mediation result supports a role for information-processing mechanisms, while the non-significant moderated mediation indicates that learning capability shaped the AI–transparency link without significantly changing the overall indirect pathway to board performance. Together, the results suggest that AI-enabled supervision may be most closely connected to stronger transparency and supervisory performance, even when organizations differ in their capacity to learn.

Subject of Research: How organizational AI empowerment relates to information transparency and supervisory board effectiveness

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

Article References: Qin, R., Qin, J., & Wang, S. (2026). AI empowerment and supervisory board effectiveness: Evidence from an information processing framework. PLOS One, 21(10), e0360152. https://doi.org/10.1371/journal.pone.0360152

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360152

Keywords: artificial intelligence, supervisory boards, information transparency, organizational learning, corporate governance, information processing, survey research, moderated mediation, empowerment, supervisory, board, effectiveness