(untitled) (Zien Journal of Social Sciences and Humanities, 2026)
The research examines the influence of Artificial Intelligence (AI) on trade finance operations, emphasizing efficiency, compliance, risk management, and inclusion. Trade finance, which facilitates worldwide commerce via instruments including letters of credit, guarantees, and supply chain financing, has historically been limited by paper-based processes, elevated compliance expenses, and susceptibility to fraud. The aforementioned inefficiencies exacerbate the ongoing global trade financing deficit, estimated at USD 2.5 trillion, disproportionately impacting small and medium-sized firms (SMEs). This study employs a mixed-methods approach, using secondary data from international organizations and empirical studies, with survey evidence from 120 stakeholders in banking, SMEs, and regulatory authorities, to analyze the potential and obstacles associated with AI adoption. The findings demonstrate that AI increases efficiency via automated documentation, boosts fraud detection using anomaly-based models, and fortifies credit risk assessment using predictive analytics. Participants recognized expedited document processing (82%) and enhanced fraud detection (76%) as the primary advantages. Nonetheless, obstacles like elevated implementation costs (68%), insufficient technical competence (64%), and legal ambiguity (55%) hinder adoption, especially for small and medium-sized enterprises (SMEs). The discourse underscores that whereas banks and corporations are progressing in AI integration, SMEs persistently encounter structural obstacles, prompting worries over inclusion. The paper suggests that AI might revolutionize trade finance processes and reduce the global trade finance deficit, provided that adoption hurdles are mitigated. Recommendations include investments in digital infrastructure, focused assistance for SMEs, open regulatory frameworks, and the harmonization of cross-border policies to facilitate equitable and sustainable AI use in trade finance.