Abstract

In recent years, artificial intelligence (AI) has witnessed significant development in economic applications, particularly in the field of foreign trade, which relies heavily on accurate data to support decision-making and policy formulation (WTO, 2025). This study is significant because of the global need to improve trade data quality and align with digital transformation in economic information systems (UNCTAD, 2025).
The Objectives of this study are examining the role of AI in collecting and processing foreign trade data, highlight the advantages of AI over traditional methods and providing practical recommendations for implementing AI in statistical and trade institutions.
This study adopts a descriptive-analytical approach, based on a review of recent literature and analysis of international experiences from organizations such as WTO, UNCTAD, and Eurostat (Eurostat, 2024).
The study indicates that AI can improve data quality, accelerate collection and processing, reduce human errors, and support trade forecasting, while emphasizing the need for digital infrastructure, trained personnel, and supportive regulatory policies.