Study of ESG transformation of the region by the artificial intelligence system - Lomakin, Nikolay I.; Kuzmina, Tatyana I.; Maramygin, Maxim S.; Yurova, Olga V.; Minaeva, Oksana A.; Polozhentsev, Aleksey A.; Eliseeva, Tamila D. (Nauka Krasnoi͡a︡rʹi͡a, 2025)
The theoretical aspects of the ESG transformation of the region in modern conditions are studied. The relevance is due to the fact that in the conditions of technological transformations, rapid introduction of innovations, increasing market uncertainty, artificial intelligence systems are increasingly used to achieve sustainable development on ESG principles. The goal is to identify patterns of ESG transformations of the region by the artificial intelligence system and obtain a forecast value of the gross regional product for the next year. In the course of the study, a deep learning model DL "Random Forest" was formed, which allows you to get a forecast of the gross regional product of the Volgograd region. The novelty is due to the fact that the work put forward a hypothesis, which was successfully proven, regarding the fact that forecasts of the gross regional product for the next year can be obtained using the deep learning model DL "Random Forest", which largely predetermines the dynamics of sustainable development of the region. The conclusions of the study are that the DL-model "Random Forest" has been developed, which calculated the forecast values ​​of the gross regional product. The forecast value of the GRP for the first option was 1305.88 billion rubles, which is 4.47% more than the actual value in 2024. The forecast value of the GRP for the second option will be 1361.76 billion rubles, which is 8.94% more than the actual value in 2024. The scope of application of the obtained results is the real sector of the economy, local government planning bodies. EDN: HYQANI