Generative AI and Marketing Scenario Migration in Cross-Border E-Commerce: Evidence from US and Southeast Asian Markets

Abstract

The escalating deployment of generative artificial intelligence, specifically Artificial Intelligence Generated Content (AIGC), has introduces an unprecedented operational paradigm for internationalizing enterprises seeking to transplant mature domestic e-commerce strategies into heterogeneous culturally differentiated jurisdictions. This paper constructs a comprehensive framework evaluating how AIGC-driven localization facilitates structural scenario migration, thereby stimulating consumer adoption and long-term market growth within the distinct digital ecosystems of North America and Southeast Asia. Utilizing a mixed-methodological approach that couples multi-channel web-scraped behavioral telemetry with structured cross-national panel data, we parameterize the hidden relational trajectories among automated semantic adaptation, visual aesthetic translation, and peripheral consumer conversion dynamics. The empirical investigation revealed that the linear structural assumptions frequently celebrated in initial pilots frequently encountered substantial empirical frictions; sharp data variations and acute localized linguistic misalignment emerged during early implementation phases, forcing substantial recursive contextual calibrations within our empirical modeling. The structural equation estimations indicate that AIGC-driven adaptation, to some extent, compresses the perceived psychological distance of foreign consumers, although its explanatory variance exhibits pronounced geographical heterogeneity conditioned by regional regulatory environments and varying digital literacy levels. Competing interpretations of these empirical anomalies suggest that elevated customer conversion metrics might remain partially dependent upon transient novelty effects or unobserved macroeconomic consumption shocks rather than purely endogenous algorithmic efficacy. Considering the inherent conceptual black-box of deep learning semantic generators, further research is critically needed to unpack the precise ethical and cultural boundaries governing automated cross-border governance.