Artificial Intelligence in Agricultural Engineering as A Factor in Ensuring the Economic Security of Enterprises

Abstract

This article examines the current application of artificial intelligence (AI) in agriculture, which contributes to the economic security of enterprises. It analyzes the growth rate of the global AI market in the agricultural sector, as well as the scale and dynamics of AI technology implementation in domestic and international agricultural companies. The study is based on a comprehensive analysis of tabular statistical data and a comparison of regional and industry indicators, using market reports from leading research companies and data from government and industry sources. It examines technological solutions from domestic and international companies, as well as government support mechanisms and infrastructural aspects of AI implementation. Key AI technologies include machine learning (47% of the market), computer vision (25%), and robotics (4%), used in precision farming, crop monitoring, yield forecasting, and risk management. Domestic developments, such as Cognitive Pilot and Sber Business Soft, demonstrate effective solutions adapted to Russian conditions. International leaders (John Deere, Bayer, IBM, Microsoft) demonstrate impressive results in increasing yields (up to 25%), reducing water consumption (up to 30%), and reducing pesticide use (up to 90%). The main barriers to implementation remain high initial costs, a shortage of qualified personnel, and infrastructure limitations, particularly in Russia. This article highlights the short-, medium-, and long-term development prospects for the industry, focusing on the expanded use of autonomous equipment, generative AI, and biotechnology. The use of artificial intelligence in agricultural engineering is rapidly growing and has significant potential for transforming agriculture. The economic efficiency of these technologies is demonstrated by increased yields, reduced costs, and a rapid return on investment, which contributes to the economic security of enterprises.