BENEFITS AND CHALLENGES OF ARTIFICIAL INTELLIGENCE IN TRANSPORT LOGISTICS: A SYSTEMATIC LITERATURE REVIEW

Abstract

In the transportation sector, the search for greater efficiency has made Artificial Intelligence (AI) a technology with great transformative potential. However, its practical application faces significant challenges. This study investigates, through a systematic literature review, the main benefits and obstacles of AI in transportation logistics. The methodology used involved a structured search for articles published between 2020 and 2024 in the Google Scholar and SciELO databases. To this end, rigorous inclusion and exclusion criteria were applied, resulting in the selection and full analysis of 10 relevant articles. The results show that process optimization and cost reduction are the most cited benefits, while high initial investment and the need for high-quality data are the most significant challenges. Additionally, the relevance of technical and organizational barriers in the sector was identified. It is concluded that there is still a gap between the great theoretical potential of AI and its real practical feasibility. This work aims to contribute by consolidating the current scenario, providing information for future implementations in the sector, as well as suggesting pathways for new scientific studies.