ARTIFICIAL INTELLIGENCE AND ARBITRATION IN THE MIDDLE EAST: AN EMPIRICAL COMPARATIVE STUDY OF JORDAN AND BAHRAIN USING TAM

Abstract

Artificial intelligence (AI) is increasingly being integrated into professional services, yet its application in arbitration remains underexplored, particularly in emerging economies. This study investigates the factors influencing AI adoption in arbitration in Jordan and Bahrain, extending the Technology Acceptance Model (TAM) with institutional and ethical dimensions. Using survey data from 170 respondents in Jordan and 142 in Bahrain, and applying Partial Least Squares Structural Equation Modeling (PLS-SEM), the research tests both mediating and moderating relationships. The results show that adoption pathways differ across the two contexts. In Jordan, adoption is primarily shaped by trust, security, and ease of use, reflecting a cautious and risk-sensitive approach. In Bahrain, adoption is driven by usefulness, transparency, and regulatory support, underscoring the role of governance maturity. Attitudes were found to mediate the influence of usefulness, trust, and transparency on behavioral intention, while regulatory support strengthened the translation of intention into actual use. These findings contribute to theory by extending TAM to legal and ethical domains and highlight the importance of institutional maturity in shaping adoption outcomes. Practically, the study offers tailored recommendations for policymakers, arbitrators, and technology developers in fostering responsible AI adoption in arbitration.

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