Today, digitalization has become an urgent need for logistics companies. Artificial intelligence (AI) increases the competitiveness of the carrier and enhances its customer centricity. Currently, the main applications of AI include intelligent routing, taking into account hundreds of factors – from traffic jams to road conditions, predictive maintenance of equipment and monitoring the attention of drivers. Also, autonomous vehicles, including unmanned trucks, are gradually moving from the testing stage to commercial operation. Their comprehensive testing on public highways is planned for the current year.
Foreign retailers and logistics operators in countries with developed e-commerce, such as the United States, China, Germany and Sweden, are active drivers of innovation in the field of commercial vehicles. They see AI as a strategic tool to improve competitiveness. They are introducing comprehensive platforms that not only automate transportation planning, but also provide end-to-end supply chain transparency, as well as data mining to predict demand. Particular attention is paid to solving the “last mile” problem and optimizing returns of goods. Advanced companies use AI-vision to assess automatically the status of returned products and chatbots to accompany the client, which significantly speeds up processes and reduces operating costs. These investments are aimed at creating a more sustainable and customer-oriented logistics ecosystem.
Today in Russia a whole range of solutions is being developed by the largest domestic transnational IT company, which represents an extensive ecosystem of digital services. In particular, the Router service is actively used by logistics companies; for example, it became possible to replace the work of 10 logisticians of the federal 3PL operator.
The key value of AI is in the direct impact on spending items. Already today, one of the domestic logistics companies specializing in express delivery of goods and documents, which has implemented AI to optimize courier routes, has achieved 15% rationalization of planning processes. Algorithms that analyze traffic jams, order density and fuel consumption build the most efficient paths, which directly reduces gasoline costs and delivery time. The same principle works in backbone logistics. In particular, a large multi-format retailer, as a result of the large-scale introduction of the Veeroute automatic routing system, received a 2-5% reduction in the cost of delivering one pallet seat.
Another layer of the economy is the prevention of unscheduled expenses. The technology of predictive maintenance introduced by the domestic manufacturer of heavy trucks based on the analysis of data from sensors made it possible to predict breakdowns of heavy trucks. This reduces transport downtime by 15%, saving money on urgent repairs and lost contracts. The Antison monitoring system, which is used by Mosgortrans, solves the problem of driver overwork. Its implementation made it possible to reduce the accident rate by 26-30%, which directly reduces the colossal costs of vehicle repairs, legal costs and insurance payments.
Large-scale technology proliferation is hindered by serious barriers. The key challenge is the low level of digitalization and the lack of structured data in a significant part of the market, especially in the segment of small and medium-sized businesses (SMEs), which makes up about 70% of the industry. According to digital logistics experts, most of the main carriers are still working with paper documents and Excel, which does not allow the use of AI algorithms that require large amounts of data for training. While the neural network allows to speed up the processing of extremely important workflow for the industry, confirming the legitimacy of the cargo, optimizing the process, from processing invoices to customs declarations.
For companies, the introduction of AI is a complex transformation that requires investment in software, hardware and personnel training. Additional factors of pressure on the business are an increase in the cost of transportation and a shortage of personnel, which leads to market consolidation. In addition, the regulatory environment, according to market participants, is tightening, which increases the burden on the business. Nevertheless, the state provides support to entrepreneurs through national projects, such as the Digital Economy, and stimulates the transition to electronic transportation documents (ETD), which will become mandatory from September 1, 2026.
It should also be noted that the introduction of unmanned vehicles in Russia is moving from the stage of theoretical discussions and local experiments to the phase of forming a systematic state strategy and preparing for mass commercial operation. The prospects for this direction are determined by three key factors: the creation of a comprehensive legal framework, active practical tests and the obvious economic effect on logistics.
In January 2026, the Ministry of Transport of Russia presented a bill “On highly automated vehicles” (HAV), which is designed to create permanent, not experimental rules of the game for all participants in the logistics market. The document introduces important concepts, such as “remote driver,” and clearly distributes responsibility between the car manufacturer, software developer, owner and operator. The official goal of the regulator is to ensure the release of level 5 drones on public roads by 2028. At the same time, the department predicts that by 2050 up to half of all transport in Russia may become unmanned.
Today, Russia is not waiting for the adoption of a law to start testing. The country has a large-scale program for the creation of “unmanned logistics corridors.” Already today, 95 autonomous trucks run along the tracks of the Neva M-11 and the Moscow Central Ring Road, which have accumulated millions of kilometers of trouble-free mileage under the monitoring of the ERA-GLONASS system. In 2026, it is planned to expand testing on the Vostok M-12 track and, most importantly, to begin testing trucks without a person in the cab completely. At the same time, pilots are developing in specific niches: from autonomous ferries and airfield tractors to delivery robots in cities.
In Russia, the prospects for the introduction of AI are largely related to import substitution, the creation and development of domestic IT platforms. At the same time, despite the state support of the industry, it is predicted that in the near future we should expect a deepening of differentiation in the logistics market. Large retailers and operators with resources and data will increase implementation, gaining an increasing competitive advantage. For small and medium-sized businesses, the main way will be to use ready-made cloud services and ecosystems that will allow them to receive analytics without having their own big data. Success will depend on the speed of digitalization of basic processes, especially the transition to ETD, which will create the necessary data base for the future application of intelligent algorithms. Consequently, the introduction of AI in Russia will deepen the existing gap between technology leaders and the rest of the market, defining a new competitive border in the logistics industry.
By Alexey Tuzov, independent expert in the transport industry