Barriers for the AI Adoption in Maritime Logistic Sector in Sri Lanka

Abstract

The seamless integration of new technologies, including Artificial Intelligence (AI), into maritime logistics operations presents significant opportunities for optimizing efficiency and competitiveness in Sri Lanka's maritime logistics sector. This study assesses the impact of critical barriers to AI adoption across four key categories: technological, organizational, financial, and industrial barriers. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and a structured questionnaire survey with 133 industry experts, the research identifies the most significant barriers, such as limited data-driven decision-making (technological), lack of coordination and support from upper management (organizational), and high implementation costs (financial). Among these, technological barriers were found to have the highest impact on adoption, followed by organizational barriers. Conversely, industrial barriers, such as lack of regulation and privacy concerns, were less significant in the Sri Lankan context. The findings provide actionable recommendations, including prioritizing investment in digital infrastructure, fostering workforce development through targeted training programs, and enacting regulatory reforms to mitigate barriers. This research contributes to theoretical and practical understandings of AI integration in maritime logistics, offering a pathway for Sri Lanka to enhance operational efficiency and compete effectively in the global trade ecosystem.