AI - Driven Data Assets Risk Management and Response Mechanisms

This paper provides an in-depth discussion of issues and mechanisms pertaining to the management of risk associated with data assets in the context of the widespread application of artificial intelligence technology. The paper's approach is twofold. It describes the relevant knowledge of data assets risk management and the basis of AI technology and it applies risk management theory to analyse the typical risks faced by data assets, such as security, quality, and compliance. The paper then goes on to propose corresponding coping mechanisms. The case study of "AI-driven Data Asset Risk Management Practices in Jingdong" illustrates the significance of effective data assets risk management for businesses and organisations and the pivotal role of AI in this context. It is anticipated that the findings of this paper will serve as a catalyst for the development and implementation of AI technologies within business enterprises.