Decision-making models in information management systems of agro-industrial enterprises

The relevance of the stated subject is determined by the wide spread of information intelligent systems (IIS) in various spheres of modern science, technology and industry, and the need to develop and implement effective algorithms for decisionmaking based on IIS technologies in the agricultural sector of the economy of the Republic of Kazakhstan. The main objective of the study was to propose a model of managerial decision-making in the agrarian sector of Kazakhstan. The methodological approach here was based on the combination of methods of a comprehensive study of the key principles of decision-making in information management systems and an analytical study of the current prospects for the practical application of artificial intelligence technologies in the processes of enterprise management in the agroindustrial complex. Methods of analytical comparison and synthesis of data gathered during the study were also used. The findings obtained determine the main tasks of decision-making methods in the information networks of management of enterprises in the agricultural sector of the Republic of Kazakhstan, considering the current issues in this area and practical options for their resolution. The study revealed that, between 2000 and 2024, the average yield of all crops increased by 153%, with significant improvements observed in oilseeds, sunflower seeds, and potatoes. The study also observed a substantial increase in the use of information and communication technologies in Kazakhstan, with a nearly 3.5-fold rise in related expenditures. Furthermore, the research highlights the potential for automation in the agricultural sector, particularly in enhancing resource utilisation and boosting productivity. The practical significance of the findings lies in their implementation in the activities of enterprises in the agricultural sector to create effective management systems, leveraging artificial intelligence technologies. These developments will support the further modernisation of the sector, contributing to its economic sustainability and alignment with global trends in digital transformation