## 2 Literature Review  
A preliminary review of the existing scientific literature was conducted with the aim of assessing the application of artificial intelligence in the field of logistics, as well as examining its related advantages and disadvantages. The literature review was carried out using two scientific databases: IEEE Xplore and Science Direct. The search strings were formulated using two main categories of keyword. The first category is related to artificial intelligence, for which various synonyms were used, including artificial intelligence, artificial reasoning and automation, in order to identify the widest possible spectrum of items. The second category of keywords is associated with the supply chain. This term, having been at the heart of numerous strategic initiatives, has driven the use of terms such as logistics, supply chain, goods entry and shipping notes. The application of this search string in the previously mentioned search engines, together with the restriction to publications in journals or conferences, resulted in 62 references. As a result, duplicates and publications dealing with topics such as programmable logic controllers, robotics, energy management, information systems and maintenance were eliminated. At the end of this process, only 15 references were deemed relevant for the present study. The management of logistics and supply chain has established itself as a fundamental element of global operational strategy in the context of the 21 st century global market and business operations. The role of logistics, particularly 3 PL, has become of paramount importance for companies that want to achieve success in sustainable global business operations [9]. Over recent years, artificial intelligence (AI) techniques have proved to be a promising solution for optimizing production processes and maintaining competitiveness [10]. This article aims to examine the advancements and implications of employing artificial intelligence for the improvement of internal logistics, particularly with reference to the phase of goods receipt and processing of shipping notes. Research on artificial intelligence began in the 1950s. The term was coined by [PERSON] at the Dartmouth Conference in 1956 and it marked the official birth of AI as a field of research. From the time the first computer studies were developed, artificial intelligence has continued to develop more and more, leading to the first industrial applications of strong and weak artificial intelligence as early as the 1980s. In the recent literature, there are several contributions dealing with the applications of artificial intelligence in logistics, identifying its capabilities and in the very management of the entire supply chain, through a systematic arrangement and main challenges and benefits. For example, some authors demonstrate how current artificial intelligence capabilities result in improving supply chain management, especially nine main capabilities that contribute significantly: planning, analysis, modeling, monitoring, control, automation, autonomy, problem solving and decision making [11]. In relation to the resolution approaches of artificial intelligence, machine learning and multi-agent methods appear to be the most prevalent for the supply chain activities that are delineated in this study. It is noteworthy that the number of applications employing artificial intelligence techniques is considerably limited. Given that artificial intelligence constitutes one of the nine technological pillars of Industry 4.0, this outcome is somewhat unexpected. The expansion of the list of parsed references through the formulation of additional search strings also presents a potential avenue for future research [12]. In the literature, there are several significant subjects that necessitate further exploration and enhancement by artificial intelligence researchers.