The aim of this research is to investigate barriers and challenges associated with Artificial Intelligence (AI) adoption and implementaion in logistics operations.A systematic literature review was conducted to assess the major catogries of challenges as well as specific challenges for each category puplished in peer-reviewed articles that are relevant to logistics operations. A total of 114 articles from six (6) electronic databases (i.e., IEEE Xplore, Science Direct, Elsevier's Scopus, Web of Science. Springer link, Google Scholar) were analyzed.  Based on the findings, major categories of barriers and challenges of AI adoption and implementation in the logistic are identified as follows: (organisational and managerial challenges, technological challenges, economic challenges, data challenges, environmental challenges, social challenges, and political, legal, and ethical challenges). Seven (7) categories, 16 specific challenges such as lack of top management support, internal requirement-organizational strategy, real-time response, disconnected systems, technology complexity, skill and expertise, high investment, operational costs, AI infrastructure, data standardization, scalability factors, data privacy and security, and insufficient operational warehouse space were identified. This research provides a further benchmark for decision making for logistics operation managers to deal with challenges and barriers in the adoption of AI in supply chain management.