The scientific paper presents the authors’ research on the aspects of nature and process of forming a new direction in the management system of sustainable development – green management. This direction which has recently become quite popular has been declared as a new priority in the implementation of large projects. But so far there is no practice of implementation and regulatory approval of this concept. It is generally accepted that green management is based on the principles of a lean or green economy and harmless attitude to the natural environment. From the authors’ point of view, this concept should be interpreted slightly broader, since regular monitoring of the state of the environment should be based, among other things, on the introduction and wide spread of information technologies into the management system.

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Neural networks have proven to be highly adaptable to various tasks associat-ed with large data sets and their processing in order to obtain new knowledge and data for subsequent planning of the development of various systems. Neural networks are used not only in the processing of large data sets, but also in the construction of predictive models. In this article, we built a neural net-work model for calculating and forecasting profit index of the agro-industrial complex (AIC) of Russia, on the basis of aggregated input factor parameters, reflecting the potential of the industries. In addition to the neural network forecast, the article builds a profit forecast using the method of regres-sion-correlation analysis, which has long been used by economists. For fore-casting purposes, the analysis of the dynamics of development of the branches of agro-industrial complex was carried out and the main factors determining their future opportunities were selected. Using the online platform Deductor Studio Academic assessed the dependence and impact of input indicators on the derived profit indicator and checking the correlation coefficients between the parameters were calculated. The obtained forecasted profit values were com-pared with the actual profit value and the difference in the accuracy of the forecasts was calculated.

National food systems are constantly exposed to external triggers that reduce their resilience and integrity. The COVID-19 pandemic has shown the vulnerability of many food systems that do not have a sufficient margin of safety and resilience, which requires the introduction of additional government support measures and stimulation of food production and transportation to destinations. The expanded concept of food security allows a more multifaceted look at this concept and reveal its essence. Assessment of existing external triggers and their clear identification will allow in the future to minimize their impact on the state of sustainability of the national food system.