ARTIFICIAL INTELLIGENCE AS A TOOL FOR INTERNAL CONTROL OF GRAIN PRODUCTION COSTS

Subject/topic. Grain production, being a complex and resource-intensive system, requires effective management at all stages of the production cycle. In this article, the subject of research is internal cost control, a critical element for optimizing the use of resources and increasing the economic efficiency of agricultural enterprises. The research topic is the use of artificial intelligence (AI) as a tool that can qualitatively change the processes of internal cost control in grain production. Goals/objectives. The purpose of this article is to develop recommendations for improving the methodology for internal control of costs for the production of grain products using artificial intelligence. As part of the study, the following tasks were set and solved: to analyze the existing methods of internal control of costs in grain production, to identify their shortcomings; determine the possibilities and advantages of using AI to solve internal control tasks; develop a methodology for the use of AI for the analysis, monitoring and forecasting of costs for the production of grain crops. Methodology. The analysis of theoretical and methodological aspects of the organization and implementation of internal control in agricultural organizations is devoted to the works of Shatina E.N., Kozmenkova S.V., Frolova E.B. [1], Azarskaya M.A. [2], Zakirova A.R., Klychova G.S., Ziganshina B.G., Khoruzhiy V.I., Nigi matullina N.N. [3] et al. As a research tool, such general scientific methods as a systematic approach, comparison, a method of systematization and generalization of data were used. The informational basis of this study was the works of domestic and foreign scientists devoted to improving the internal control system. Results. As a result of the study, working documents for internal control of the cost of producing grain crops using AI have been developed, which will optimize the implementation of control measures. Scope of the results. The practical significance of the study lies in the possibility of applying the developed recommendations when conducting internal control of the costs of producing grain crops using artificial intelligence in order to increase the effectiveness of control measures. The implementation of the proposed recommendations on improving the methodological support of internal control of costs for the production of grain crops will make it possible to form an objective conclusion on the results of the audit and provide the management of the agricultural organization with information for making management decisions. Conclusions/significance. Having studied the existing methods of using artificial intelligence in internal cost control, we found that they did not pay enough attention to the systematization of the results of control procedures. In this regard, we have developed working documents of internal control using AI, allowing to optimize the organization and implementation of control measures