Artificial Intelligence in Commercial Arbitration: Applications, Challenges, and Pathways

Abstract

With the rapid development of artificial intelligence (AI) technologies, their application is gradually permeating the field of commercial arbitration. Commercial arbitration, characterized by flexibility, confidentiality, and efficiency, shares a natural affinity with AI. AI has demonstrated significant utility in enhancing arbitration efficiency and optimizing arbitration processes—for example, employing natural language processing (NLP) techniques for case text analysis, and leveraging data mining and machine learning algorithms to provide reference points for arbitral outcomes. However, the integration of AI into commercial arbitration also faces considerable challenges. These include technical issues such as algorithmic opacity, reliability, and stability; legal concerns regarding data privacy protection and the risk of algorithmic discrimination; and industry-level challenges related to stakeholder acceptance and insufficient talent development. In response to these challenges, this paper proposes pathways including promoting research on algorithmic transparency, improving data privacy regulations, and strengthening industry training, with the aim of providing theoretical support and practical guidance for the application of AI in commercial arbitration.