25% of agricultural enterprises collect data on economic activity automatically

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This was reported by representatives of the Geomir company at the international forum Kazan Digital Week. They noted that 35% of all Russian farms are at the stage of normalizing normative and reference information (NSI). Bringing data to uniform standards allows improving the processes of analysis and decision-making. According to the assessment of Geomir JSC, 30% of domestic agricultural producers have advanced further and have already moved on to collecting all data on the farm in a single system.

. However, 23% of agricultural cayman islands whatsapp resource producers still analyze it manually, and only 3% have moved on to the stage of automatic data analytics with recommendation services.

"The implementation of digital solutions is happening in stages. We see that the next significant leap in the transformation of the industry may occur when manufacturers who have already automated data collection move to the same automatic method of processing and analyzing it. We expect this to happen in the next few years," said Alexander Komlev, Sales Director of Geomir JSC.

Only 2% of agricultural enterprises in Russia use artificial intelligence and computer modeling to optimize production processes. According to Geomir representatives, a more dynamic penetration of these technologies is held back by the lack of necessary personnel and fears of investing in the agro-industrial complex (AIC).

Alexander Komlev identified four main areas of application of artificial intelligence (AI) in the agro-industrial complex: predictive models; recommendation models; modeling of production processes; image recognition (satellite images, images from drones and mobile devices).

A representative of the press service of JSC Agroholding Steppe told how things are going with digitalization at the enterprise: "In the Agroholding Steppe, the process of collecting the vast majority of data is automated. Analysts additionally process the collected information. We create digital twins of fields, successfully test sowing according to 3D models based on geospatial data, use cloud services with AI in various areas, including when forming crop rotation, calculating crop margins, and agrotechnical operations. We plan to focus on systems for recognizing pests and weeds in fields and gardens, and assessing the condition of soils based on space images. To improve the quality of NSI, the agroholding has a special department. In general, the digitalization process in the agro-industrial complex in Russia is not dynamic enough. At the same time, in some companies that have been actively and for a long time investing in digitalization, there are breakthroughs in this direction, and the automation of processes remains at a high level."

Independent expert on IT and telecom markets Vadim Plesskiy explained the reasons for the low percentage of digitalization in the Russian agro-industrial complex: "Digitalization is an expensive process, and its effect in the agro-industrial complex is not obvious. There is a personnel gap between the village and the city, and it is quite significant. This is nothing new - there was a noticeable difference in personnel training during the Soviet era. It will not be possible to satisfy the personnel shortage in IT specialists in rural areas - they have no motivation to come to rural areas, and agro-industrial complex enterprises are not ready for the remote work format. In addition, there is a very large gap between what can be offered in terms of wages in the agro-industrial complex and the expectations of specialists. Therefore, in the near future, many farms will continue to "count in Excel", and this will not be the worst option compared to manual paper accounting. To change the situation, a radical increase in salaries in the agro-industrial complex is necessary. But, judging by the statements of the owners of agro-industrial complex companies, this is not included in their plans at the moment."