AI-Driven Risk Management for Sustainable Enterprise Development: A Review of Key Risks

The proliferation and application scope of artificial intelligence (AI) have witnessed a gradual expansion in the last several years, marking a substantial leap in quality when compared to the landscape a decade ago. Its permeation into every industry is undeniable, yet it concomitantly poses a multitude of challenges that are inherently difficult to fully mitigate across various domains. By harnessing the power of AI, enterprises can significantly augment their risk identification and management capabilities, ultimately fostering sustainable development. The implementation of AI technologies facilitates automated analysis of complex data sets, rapid identification of potential risk points, and offers precise early warning systems along with invaluable decision support. However, it is imperative to acknowledge that AI itself is not without risks. The rapid pace of its development has been accompanied by a proliferation of incident reports, highlighting the wide range and intricate nature of the risks involved. The unfortunate instances of technology companies succumbing to bankruptcy further underscore the fact that the development and utilization of AI are not devoid of vulnerabilities, thereby posing latent threats to the sustainable development of enterprises. Consequently, this paper adopts a rigorous literature review method, carefully selecting 82 highly pertinent articles, to comprehensively synthesize and analyze the drawbacks and risks associated with AI applications in recent years. The ultimate aim is to provide insightful guidance for the sustainable growth of enterprises and the efficient harnessing of AI technologies.