Privacy Protection in the Application of Artificial Intelligence Technology in Corporate Governance

This study investigates the application of AI in corporate governance and capital investment, drawing on case studies from multiple jurisdictions—including the EU, China, and the U.S.—and focusing on financial, regulatory, and strategic data. The implementation of advanced privacy-preserving technologies, such as differential privacy and federated learning, resulted in a 64% reduction in data breaches, a 12% decrease in regulatory fines, and a 16% increase in client retention. Stakeholder feedback indicated significant improvements in audit readiness (89%) and overall trust (84%). While these technologies enhance compliance, transparency, and operational efficiency, challenges related to computational costs, system compatibility, and scalability remain. The findings underscore the importance of adopting an integrated privacy governance framework that combines robust technical solutions with organizational and regulatory strategies to effectively safeguard data in AI-driven corporate environments.

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Publication Details

Journal
International Journal of Information Security and Privacy
Published
2025-10-02
DOI
https://doi.org/10.4018/ijisp.389733
Primary Topic
Digital Transformation in Law
Type
article
Field-Weighted Citation Impact
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article

Privacy Protection in the Application of Artificial Intelligence Technology in Corporate Governance

Fei Zhai, Tao Zhang, Mengjun Xu
International Journal of Information Security and Privacy
Digital Transformation in Law
article

Privacy Protection in the Application of Artificial Intelligence Technology in Corporate Governance

Fei Zhai, Tao Zhang, Mengjun Xu
article en

Abstract

This study investigates the application of AI in corporate governance and capital investment, drawing on case studies from multiple jurisdictions—including the EU, China, and the U.S.—and focusing on financial, regulatory, and strategic data. The implementation of advanced privacy-preserving technologies, such as differential privacy and federated learning, resulted in a 64% reduction in data breaches, a 12% decrease in regulatory fines, and a 16% increase in client retention. Stakeholder feedback indicated significant improvements in audit readiness (89%) and overall trust (84%). While these technologies enhance compliance, transparency, and operational efficiency, challenges related to computational costs, system compatibility, and scalability remain. The findings underscore the importance of adopting an integrated privacy governance framework that combines robust technical solutions with organizational and regulatory strategies to effectively safeguard data in AI-driven corporate environments.

International Journal of Information Security and PrivacyVol. 19(1)
Jiangsu University of Science and Technology (CN)
Openalex Percentile: Top 56%
Digital Transformation in Law
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Privacy Protection in the Application of Artificial Intelligence Technology in Corporate Governance — Fei Zhai, Tao Zhang, et al. · International Journal of Information Security and Privacy (2025) | TGRS Research Map | TGRS