The article investigates the impact of digitalization and big data technologies on the development of agriculture. Based on a literature review, key trends in the application of big data in the agricultural sector, including precision farming, smart farms, yield forecasting, and supply chain optimization, were identified. The empirical part of the study is based on survey data from Russian farming enterprises (n = 500) as well as an analysis of case studies on the implementation of digital solutions by large agricultural holdings. The main findings indicate a significant potential for big data to enhance the efficiency and sustainability of agriculture. It was found that the use of predictive analytics based on big data allows for a 15–20% increase in yield, a 10–15% reduction in storage losses, and a 20–25% optimization of resource costs. However, key barriers remain, such as a shortage of expertise in data science, high technology costs, and resistance to change. The conclusion highlights the need for state-level support for the digital transformation of agriculture, as well as the development of partnerships between science and business to create and transfer innovative solutions.
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S. G. Eremin (2025) studied this question.