<![CDATA[Artificial Intelligence (AI) is increasingly reshaping international business law by transforming how firms manage regulatory compliance, governance processes, and cross-border trade operations. In practice, AI is applied to legal mechanisms such as automated customs compliance, regulatory monitoring, sanctions screening, and cross-border data transfer governance. Despite growing adoption, empirical evidence remains limited on how AI deployment and institutional conditions jointly influence compliance effectiveness and international trade performance. To address this gap, this study examines the effects of AI adoption, regulatory clarity, digital infrastructure readiness, and cross-border data governance quality on international trade performance, with compliance effectiveness as a mediating mechanism. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on 350 survey responses, the findings show that all four antecedent factors have a significant positive impact on compliance effectiveness. Compliance effectiveness, in turn, strongly enhances firm-level international trade performance, measured through improvements in trade efficiency, risk reduction, and market expansion. Moreover, compliance effectiveness significantly mediates the relationship between the institutional and technological factors and trade performance. Among the predictors, cross-border data governance quality exerts the strongest influence. These findings highlight that AI-enabled trade outcomes depend not only on technological adoption but also on regulatory clarity, robust digital infrastructure, and harmonized data governance frameworks, offering practical insights for policymakers and firms integrating AI into international business law.]]>
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