The digital transformation of Ukraine’s agricultural sector represents a strategically important development pathway, enabling the optimisation of management processes, the reduction of production costs, and the enhancement of agricultural enterprises’ productivity. This study aimed to develop a mechanism for the digital transformation of the management of agricultural sector development based on modern technological solutions and their economic efficiency. To achieve this aim, bibliographic and content analysis, economic forecasting methods, mathematical modelling of digitalisation costs, and statistical methods for assessing the effectiveness of digital technology implementation were employed. The study established that the main mechanisms of digital transformation include digital platforms, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), blockchain, and ERP systems. The total cost of digitalising Ukraine’s agricultural sector is estimated at approximately 18,900,110,000 USD. The largest financial investments are directed towards process automation (12,600,000,000 USD), particularly in robotic harvesting systems (4,200,000,000 USD), automated tractors (4,200,000,000 USD), and irrigation systems (4,200,000,000 USD). The cost of implementing IoT equipment, including sensors for monitoring soil and weather conditions, drones for aerial surveying, and automated data collection systems, amounts to 6,300,000,000 USD. Investments in big data analytics and AI algorithms range from 50,000 USD to 60,000 USD per system, while ERP systems are estimated at between 30,000 USD and 60,000 USD. Calculations indicate that the average cost of digitalising one hectare of agricultural land varies between 450 USD and 1,000 USD, depending on the level of technological integration. The proposed digital transformation mechanism envisages the integration of IoT equipment, automated systems, blockchain, and analytical tools into a unified agricultural management system. Its implementation is expected to reduce production costs by 20%-35%, increase productivity by 15%-25%, and decrease crop losses by 10%-18% through the adoption of precision farming and analytical forecasting. The practical significance of the study lies in the application of the developed model for government planning of agricultural sector digitalisation, optimisation of agricultural production costs, and enhancement of sector competitiveness
economic model; integration; advanced technologies; automation; Internet of Things; cost optimisation; productivity enhancement