Artificial Intelligence Technologies in Customs Administration: Opportunities, Barriers, and Prospects for Digital Transformation

Abstract

Introduction: The relevance of the research stems from the contradiction between the strategic commitment of the Russian Federation and the Eurasian Economic Union (EAEU) to the digital transformation of customs authorities, and the persistent barriers to introducing artificial intelligence (AI) technologies. The article aims to provide a comprehensive analysis of AI application opportunities for optimizing customs procedures, to identify the implementation barriers, and to outline the perspectives for developing intelligent solutions in customs control. It is the first time, that a systemic approach has been suggested, integrating the technological, regulatory, organizational, and human resource dimensions of AI implementation at the EAEU level. The research hypothesis: The effectiveness of AI technologies is achievable only via the simultaneous overcoming of four types of barriers: regulatory, infrastructural, human resource, and information security ones. Methodology: The research has been conducted via employing systemic and comparative legal analysis methods, drawing on the EAEU Customs Code, Federal Law No. 289-FZ, strategic documents of the Russian Federation and the EAEU, materials of the Federal Customs Service of Russia, and academic publications. The methodological framework is built on the theory of public sector digital transformation and the concept of risk-based control. Results: Four key perspectives of AI technologies application have been identified: inspection automation using computer vision; documentary control and declaration verifi cation; risk-oriented analysis and goods classification; development of “smart” border crossing points. The realization of AI’s benefits is feasible only via the comprehensive elimination of all the barriers identified. Conclusions: Introducing AI technologies requires a sequential approach, progressing from pilot projects to the automation of core operations. The key measures include: regulatory consolidation of AI system verification standards, a unified EAEU analytical platform, the modernization of IT infrastructure, as well as staff retraining courses. The findings provide a systemic foundation for the “smart customs” concept, enabling enhanced control efficiency, reduced cargo processing times, and more effective countering of counterfeit goods trafficking.