The article presents the results of research on the use of artificial intelligence, big data and blockchain technologies in agriculture in Russia. The use of these technologies opens up new opportunities to improve the efficiency and sustainability of agro-industrial enterprises. The purpose of the article is to study the features, advantages and problems of using artificial intelligence, big data and blockchain technologies in Russian agriculture, as well as to develop recommendations for solving the identified problems taking into account external factors. The research method includes a set of general economic methods such as description, comparison, comparison, analogy, classification, generalization, systematization, analysis and synthesis. The results of the study. The characteristics of digital technologies are revealed: artificial intelligence, blockchain, big data. The possibilities and advantages of using these technologies in Russian agriculture are analyzed, and problems with their implementation and use in the industry under consideration are identified: ensuring cybersecurity, violation of data confidentiality, lack of qualified personnel in the field of digital technologies for the needs of agriculture, difficulty in understanding and using technologies, resistance to change, high cost of implementation, underdevelopment of infrastructure digital technologies and a lack of data for analysis in rural and remote areas. Based on the identified problems, directions for the further development of artificial intelligence, big data and blockchain technologies in Russian agriculture were proposed. They relate to ensuring cybersecurity and data confidentiality, providing qualified personnel, eliminating resistance to change, and developing digital infrastructure. The study demonstrated that the potential for increasing transparency, trust and efficiency of agricultural enterprises determines the prospects of using these technologies in the agricultural sector of Russia.
Building similarity graph...
Analyzing shared references across papers
Loading...
Radima Malsagova
Mezhdunarodnyi sel skokhozyaistvennyi zhurnal
Financial University
Government of Russia
Building similarity graph...
Analyzing shared references across papers
Loading...
Radima Malsagova (Mon,) studied this question.
www.synapsesocial.com/papers/696c776ceb60fb80d1395bc2 — DOI: https://doi.org/10.55186/25876740_2025_68_2_220
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: