The article presents the prospects of digitalization and use of artificial intelligence technologies in the technical modernization of the agro-industrial complex (AIC). In order to improve the efficiency of agricultural industry, including the productivity and quality of products in such sectors as crop production, livestock, processing of agricultural products, a transition to innovative technologies is required. Their use in agricultural production makes it possible to significantly competitiveness of the agricultural sector of the economy of the Russian Federation. To do this, the technical modernization of the agro-industrial complex, which provides for the renewal of its base with domestic agricultural machinery is required. In modern machines, a large number of electronic systems with various sensors are involved. They allow to control the operation of various units, including the internal combustion engine, transmission, work tools and other mechanisms. The use of such systems makes it possible to reduce the cost of maintenance and use of equipment, to monitor the modes of operation and technical condition of equipment around the clock, to conduct repair and maintenance activities as required. The current global trend is the use of remote machine diagnostics systems. They allow service centers and emergency support to diagnose a vehicle at a distance, reducing downtime. In recent years, there has been a trend towards digital solutions in machine maintenance. 3D technologies are promising for repair of agricultural machinery, including restoration and hardening of parts. They can be used to measure the geometric dimensions and determine the physical and mechanical properties of part faces of agricultural machines during the incoming inspection of spare parts and fault detection of parts, by scanning them. The introduction of digital technologies and artificial intelligence in the repair practice will reduce the duration of repair and maintenance actions during the technical service of agricultural machinery and significantly reduce the cost of their implementation.