Аннотация
This article analyzes the economic mechanisms and opportunities for sustainable development of the real sector of the economy of the Republic of Kazakhstan in the context of the ESG approach and artificial intelligence tools. The aim of the study is to assess the impact of environmental, social, and governance factors on companies’ financial performance and to identify sectoral differences in ESG integration. The empirical base contains panel data for five major companies from the energy sector and manufacturing industry for the period 2021-2024, compiled from official financial and non-financial reports. The methodological framework includes the calculation of an integrated ESG index, correlation and regression analysis, as well as methods for automated extraction of ESG metrics from corporate reports using natural language processing (NLP) tools. The results show that in the energy sector ESG integration demonstrates a statistically significant positive relationship with return on assets, whereas in the manufacturing industry this effect is weaker and delayed. It is established that the environmental component has the strongest impact on financial performance in the energy sector, while in manufacturing the social and governance components are more significant. The role of artificial intelligence tools in improving the comparability and reliability of ESG data is also demonstrated. The scientific novelty of the study lies in the integration of ESG analysis with artificial intelligence tools in assessing sustainable development in the real sector. The practical significance consists in the applicability of the results for developing sectoral ESG strategies, improving economic analysis, and enhancing the quality of corporate non-financial reporting. Keywords: sustainable development, ESG approach, real sector of the economy, ESG index, return on assets, artificial intelligence, NLP analysis, corporate reporting.