Author(s)

Jinrui Zhang, Yixuan Che, Yuting Wang, Yunqing Wang

Corresponding Author

Jinrui Zhang

Abstract

In the digital era, data-driven decision-making has become essential for enhancing competitiveness, while integrating artificial intelligence technology presents both new opportunities and challenges. This paper focuses on the risk identification and control mechanism in the data-driven decision-making process of artificial intelligence technology-embedded enterprises. First, this paper delves into the possible risks, including data quality risks, such as inaccurate and incomplete data. Algorithm bias can result in unfair decision-making outcomes. Additionally, security and privacy threats put corporate and customer information at risk. Next, this study constructs a comprehensive risk control mechanism, covering data governance and ensuring the accuracy and reliability of data. Algorithm audit ensures the fairness and transparency of the algorithm. The security protection system prevents data leakage and malicious attacks. Therefore, accurately identifying and managing risks can help organizations minimize potential threats, enhance the rigor and effectiveness of decision-making, and achieve sustainable development when leveraging artificial intelligence technology for data-driven decision-making.

Keywords

Artificial intelligence technology; Data-driven decision-making of enterprises; Risk identification; Control mechanism