Abstract
Abstract. The problem of the quality of managerial decisions is one of the most acute problems of agriculture. Their quality can be improved with the use of digital technologies, including the use of artificial intelligence (AI) systems. The purpose of the study is to clarify the main stages of managerial decision-making, taking into account the use of AI systems. The scientific novelty lies in the development of a structural model for making a managerial decision, taking into account the use of AI systems, the main components of this process are identified. The research methods were the analysis of publications in the WoS scientific citation network on the topics “agriculture” and “artificial intelligence”, as well as the abstract-logical method in the analysis of the main stages of making a managerial decision. The results of the study were the determination of the composition and content of the stages of the procedural decision invariant, taking into account the use of artificial intelligence systems. The use of artificial intelligence systems allows diagnosing the occurrence of problems in crop production, animal husbandry, and technical systems at an early stage. Data collection and analysis in the process of making a managerial decision using AI systems includes direct data collection using sensors, cameras, scanners, etc., their cleaning and preliminary analysis, exploratory and statistical analysis, data modeling and interpretation of results. The use of AI systems will make it possible to operate with large data sets from agricultural production facilities, which will reduce uncertainty in making managerial decisions. The analysis of alternatives and the development of a management decision using AI systems turns off the forecasting of agricultural development indicators in a given system of constraints, the generation of alternative solutions and the choice of the optimal alternative, the acceptance or ignoring of the proposed alternatives. AI systems can be used to automate and optimize the process of implementing management decisions, monitoring and controlling management decisions. The use of AI systems to automate management decision-making processes in agriculture can help improve management efficiency.
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