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

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  • Mengjun Xu

    (Jiangsu University of Science and Technology, China)

  • Fei Zhai

    (Shanghai Zhongqiao Vocational and Technical University, China)

  • Tao Zhang

    (Jiangsu University of Science and Technology, China)

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.

Suggested Citation

  • Mengjun Xu & Fei Zhai & Tao Zhang, 2025. "Privacy Protection in the Application of Artificial Intelligence Technology in Corporate Governance," International Journal of Information Security and Privacy (IJISP), IGI Global Scientific Publishing, vol. 19(1), pages 1-17, January.
    • Handle: RePEc:igg:jisp00:v:19:y:2025:i:1:p:1-17
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