The rapid advancement of Artificial Intelligence (AI) technologies has fundamentally reshaped global commerce, with cross-border e-commerce (CBEC) emerging as a domain of exceptional transformation. This study employs a convergent mixed-methods design—integrating a structured questionnaire administered to 150 e-commerce professionals with 15 semi-structured managerial interviews—to provide an empirically grounded assessment of AI\\\'s multidimensional influence on CBEC performance. Multiple regression analysis (R² = 0.612; F = 44.23; p < 0.001) identifies AI adoption intensity as the single strongest predictor of cross-border performance, surpassing even company size (β = 0.487 vs. β = 0.213). Application-level findings reveal that automated translation/localization delivers the highest conversion rate improvement (64.3%), while customs automation yields the most substantial logistics cost reduction (31.4%). Despite these gains, high implementation costs (67.3%), talent deficits (62.0%), and data-privacy regulatory complexity (58.7%) constitute the principal barriers inhibiting broader diffusion—particularly among SMEs. Theoretically, the study extends the Resource-Based View and Technology Acceptance Model to the cross-border digital-trade context, and it offers a strategic AI adoption framework for practitioners and actionable recommendations for policymakers. The findings collectively affirm that AI is not merely an incremental operational enhancer but a foundational competitive capability reshaping the structure of international digital trade.
Ansari et al. (Thu,) studied this question.