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ORIGINAL RESEARCH article

Front. Big Data
Sec. Machine Learning and Artificial Intelligence
Volume 7 - 2024 | doi: 10.3389/fdata.2024.1447174

What Makes Bad Blood Good: Legal Regulation of Corporate Compliance in the Age of Artificial Intelligence *

Provisionally accepted
RUOHAN JIN RUOHAN JIN 1,2Qianqiang Xue Qianqiang Xue 2*
  • 1 Beijing University of Posts and Telecommunications (BUPT), Beijing, China
  • 2 Minzu University of China, Beijing, Beijing Municipality, China

The final, formatted version of the article will be published soon.

    With the development of artificial intelligence technology, it has been widely used in the daily management of large and medium-sized enterprises and science and technology enterprises, but little has been said about compliance rectification, and there are many debates in its theory and practice, and as a result, affecting the science and validity of risk assessment, which are still unsettled. Therefore, starting from the perspective of the administrative field and company management, this paper aims to analyze and prove the necessity of the development and promotion of artificial intelligence technology in corporate compliance rectification from the multi-dimensional perspectives of effectiveness, applicability, reference, and practicability, etc., to outline the principles of application in corporate compliance, and ultimately to build a stage-based picture of the application of artificial intelligence technology in corporate compliance. By creating corporate establishment registration software to track the technical indicators of intelligent compliance elements in real time, re-anchor the corporate intelligent compliance security protection reward and punishment system with the scoring system, based on which the top-level construction of science and technology is carried out around the issues of protection and regulatory risks, in the hope of benefiting the compliance development of corporate intelligent technology.

    Keywords: Corporate compliance, Artificial intelligence technology, and Digital Governance, Enterprise management, risk assesment

    Received: 11 Jun 2024; Accepted: 08 Oct 2024.

    Copyright: © 2024 JIN and Xue. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Qianqiang Xue, Minzu University of China, Beijing, 100081, Beijing Municipality, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.