AI empowerment and supervisory board effectiveness: Evidence from an information processing framework
- 1School of Business Administration, Northeastern University, Shenyang, China
- 2School of Accounting, Guangxi University of Finance and Economics, Nanning, China
- 3Personnel Office, Guangxi International Business Vocational College, Nanning, China
Abstract
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.
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BibTeX
@article{qin2026empowerment,
title = {{AI empowerment and supervisory board effectiveness: Evidence from an information processing framework}},
author = {Ruisheng Qin and Jiaxing Qin and Shiquan Wang},
journal = {PLOS One},
year = {2026},
month = oct,
doi = {10.1371/journal.pone.0360152},
url = {https://doi.org/10.1371/journal.pone.0360152},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - AI empowerment and supervisory board effectiveness: Evidence from an information processing framework
AU - Ruisheng Qin
AU - Jiaxing Qin
AU - Shiquan Wang
PY - 2026
DA - 2026/10/08
JO - PLOS One
DO - 10.1371/journal.pone.0360152
UR - https://doi.org/10.1371/journal.pone.0360152
AB - 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.
SN - 1932-6203
ER -