Introduction. The active adoption of digital tools is crucial for improving agricultural efficiency, which is fundamental to ensuring food security. The digitalisation of agricultural production is a key component of the measures for transitioning to a digital economy.
Aim and tasks. This study aims to assess the relationship between the net profit of agricultural enterprises and the number of digital products used. It also seeks to identify the factors influencing the efficiency of agricultural production.
Results. This study examines at several key factors of agricultural production. First, it considers at the share of the labour force involved in agricultural production, which has declined by 17.2% globally, 7% in the EU, and 5.2% in Ukraine. Secondly, it analyses changes in the number of workers required to produce 1% of value added from 1991 to 2023, showing a decline of 3% globally, 1.5% in the EU and an increase of 0.5% in Ukraine. Thirdly, the study assesses the level of digital skills among workers in the agricultural sector. In the EU, this level did not exceed 0.5% from 2016 to 2024, while Ukraine data is unavailable. Finally, the study includes case studies of two Ukrainian companies engaged in developing and implementing digital tools for agricultural production. The findings regarding the dependence of net profit and the number of digital instruments used revealed relatively high correlation coefficients: 0.776 for a group of 41 AGRIChain clients and 0.902 for a group of 34 Kernel Digital clients. The resulting models of net profit dependence on the number of digital instruments used (with slope coefficients of 365.9 for AGRIChain and 13.13 for Kernel Digital) indicate the potential for further refinement.
Conclusions. The establishment of a digital support system for agricultural production involves significant changes in employee competencies, a decrease in the total number of employees, and a reduction in the share of employees involved in agricultural production. Ukraine is characterised by an increase in the number of workers employed in agricultural production per 1% of added value, which is explained by structural changes in the industry. This study proposes adding metrics to statistical reporting to capture the number of digital technologies used in the production process and the number of employees skilled in using these technologies
