Ranking of Business Risks by Artificial Intelligence and Multi-Criteria Decision Making

With the ever-changing landscape of business, organizations face a multitude of complex risks that can hinder their success. Identifying and prioritizing these risks effectively is crucial for formulating robust mitigation strategies. This paper explores the integration of artificial intelligence (AI) and multi-criteria decision-making (MCDM) techniques as a novel approach to business risk ranking. We discuss the limitations of traditional risk management methods and provide a theoretical framework for leveraging AI and MCDM in generating more sophisticated and comprehensive risk rankings. The paper showcases the potential of this approach through a case study, demonstrating its application in a real-world business scenario. Finally, we address the challenges and ethical considerations associated with AI-driven risk ranking and outline future research directions in this burgeoning field.With the ever-changing landscape of business, organizations face a multitude of complex risks that can hinder their success. Identifying and prioritizing these risks effectively is crucial for formulating robust mitigation strategies. This paper explores the integration of artificial intelligence (AI) and multi-criteria decision-making (MCDM) techniques as a novel approach to business risk ranking. We discuss the limitations of traditional risk management methods and provide a theoretical framework for leveraging AI and MCDM in generating more sophisticated and comprehensive risk rankings. The paper showcases the potential of this approach through a case study, demonstrating its application in a real-world business scenario. Finally, we address the challenges and ethical considerations associated with AI-driven risk ranking and outline future research directions in this burgeoning field.

Keywords:

Ranking , Business Risks , Artificial Intelligence , Multi-Criteria Decision Making