Relevance. Using artificial intelligence (AI) systems is of particular importance in the transformation of modern Russian vegetable growing.Methods. Using the monographic method, the world and Russian practice of developing and using artificial intelligence systems is considered using the example of: CropX, John Deere, IBM Watson, AgEagle Aerial Systems, Blue River Technology, Farmwise, Taranis, Naiad Irrigation, Sustainable Agriculture Technology (SAT), Leader Technology, AgroCalypso, AgroVzglyad group of companies, Russian technologies and systems, Rostec Artificial Intelligence Competence Center, AgroBot, Kaluga Astra, Agrosystems, RosAgro, SAFMAR, AgriCo management company, Sadko agrofirm, AgroEco, AgroInvest and others.Results, A list of problems with the use of AI in vegetable growing is identified, such as: high initial costs of implementing AI; lack of qualified personnel with the necessary knowledge in the field of IT and agronomy; high probability of technical failures, leading to losses in productivity and increased costs; difficulty of integration with existing automation systems; information security of databases; difficulty of data preparation; legal and ethical risks; lack of necessary infrastructure; unfavorable climatic conditions for the operation of AI; resistance to innovations on the part of personnel. Despite the identified problems, the prospects for using AI in vegetable growing in Russia will allow: optimizing agronomic processes; improving the quality of forecasting and monitoring; increasing the level of automation; improving the quality of data processing; improving resource manageability; increasing the level of adaptation of production to market needs; increasing adaptation to storage conditions and supply chain logistics, increasing the level of information content of technological processes.Conclusion. Expanding the practice of using AI will increase the efficiency and sustainability of vegetable growing in the strategic perspective.

The sustainability of potato production in the Privolzhsky federal district was evaluated with the use of statistical methods. The effect of changes of yield and acreage on the production of the culture was evaluated. The stability of levels of dynamic series is estimated. The stability of production dynamics has been measured with the use of trend models.