ЦИФРОВЫЕ РЕШЕНИЯ В АГРОБИЗНЕСЕ: ФОРМИРОВАНИЕ МЕТОДОЛОГИИ МОНИТОРИНГА ЗЕРНОВОГО ПРОИЗВОДСТВА В УСЛОВИЯХ ТЕХНОЛОГИЧЕСКИХ ИННОВАЦИЙ

Abstract

The active penetration of digital technologies into human economic activity objectively poses the task of forming an informational space and a new technological base across the entire economic space of society. The appearance of key sectors of the national economy is changing, with an increasing portion of business processes moving into the digital environment, thereby forming a barrier-free character of exchange and consumption relationships. Among the sectors of the domestic economy, the agricultural sector (AIC) has the highest rates of digital activity growth in recent years, with its indicator in 2023 amounting to 200% relative to the average level across the economy – 131% (compared with 2016), indicating the beginning of fundamental transformations within the mode of production. The leader of the AIC is the production of grain and its processing products, collectively accounting for more than a third of the total volume of the agri-food market, hence the processes of digital solutions penetration into grain production require close attention. The key business process of grain production is the monitoring of all its elements, ensuring the quality and timeliness of management decisions at each level of added value production. The spread of business models based on digital technologies requires a new methodology of platform solutions not only at the level of technological adaptation but also restructuring, modification of established ways of conducting agribusiness, and significant organizational changes. Systematization of digital solutions approaches shows that the use of artificial intelligence significantly accelerates the digital transformation of grain production; however, for a widespread transition to intelligent monitoring methods of grain production, a number of objective conditions must be met, among them: data handling, the ability to choose a computer vision model, creation of neural network architecture, organization of training for personnel capable of making decisions on digital platforms, and the formation of corresponding psychological-behavioral client content. The implementation of these conditions, based on ongoing institutional transformations, is capable of ensuring stable growth of grain production, reducing its energy intensity, and preparing personnel with digital economy competencies.