<![CDATA[The rapid evolution of Industry 5.0 has positioned Artificial Intelligence (AI) as a critical enabler for modernizing public sector operations, including customs, yet the supporting literature remains fragmented. To address this, a Systematic Literature Review (SLR) following PRISMA guidelines was conducted to synthesize the current state of knowledge, searching the Scopus database for articles published between 2015 and 2025 initially identified 736 articles, from which a final sample of 20 articles was selected for systematic analysis. The findings revealed that the most applied AI technologies are supervised machine learning and NLP, which offer significant benefits like higher seizure hit-rates, but also face technical challenges such as data quality and concept drift. Curiously, this review identifies that the strategic potential of these technologies is critically undermined by a significant institutional gap: the absence of international standards for data, interoperability, and governance. This study's originality and value, therefore, lie in its contributions at both theoretical and practical levels. Theoretically, it shifts the scholarly focus from purely technical issues to the critical need for a global institutional framework. Practically, it provides a strategic roadmap and a direct call to action for the World Customs Organization (WCO) to lead this standardization initiative, aiming to help customs administrations worldwide advance their journey toward intelligent risk management.]]>
