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The article examines the role of artificial intelligence and machine learning technologies in optimizing planning processes at Russian industrial enterprises in the context of the digital transformation of the economy. The relevance of the study is due to the need to improve the efficiency of production planning in the context of import substitution and sanctions restrictions that require the most rational use of resources. The purpose of the research is a systematic analysis of the role of artificial intelligence and machine learning technologies in optimizing planning processes at Russian enterprises, identifying areas of application, quantifying the effects achieved and systematizing the problems of implementation. Based on the analysis of scientific literature and empirical data, the main areas of application of artificial intelligence in planning have been identified: demand forecasting, optimization of production schedules, inventory management, and multi-criteria optimization of output. It is shown that the introduction of artificial intelligence-based systems makes it possible to increase labor productivity, reduce production costs, reduce equipment downtime, and improve forecasting accuracy. Practical cases of Russian enterprises are systematized, including the experience of Magnitogorsk Iron and Steel Works, Norilsk Nickel, as well as developments by GoodsForecast and the Moscow Aviation Institute. The main problems of implementation have been identified: the quality of the source data, the shortage of qualified personnel, integration with existing IT systems, and resistance to organizational change. The conclusion about the need for an integrated approach to the digital transformation of planning, combining technological, organizational and personnel aspects, is substantiated.
Keywords:artificial intelligence, machine learning, planning, optimization, digital transformation, forecasting
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