AI Tools in the Digital Transformation Programmes of Industrial Enterprises

This article is devoted to the study of the prospects for the development and implementation of AI in industry in the context of digital transformation. Autonomous factories, integrated supply chains, and autonomous vehicles is a real proof of technological advances that AI brings to life. The artic...

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Bibliographic Details
Main Authors: N. M. Komarov, S. S. Golubev, D. S. Pashchenko, A. G. Shcherbakov
Format: Article
Language:Russian
Published: Government of the Russian Federation, Financial University 2024-11-01
Series:Мир новой экономики
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Online Access:https://wne.fa.ru/jour/article/view/442
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Summary:This article is devoted to the study of the prospects for the development and implementation of AI in industry in the context of digital transformation. Autonomous factories, integrated supply chains, and autonomous vehicles is a real proof of technological advances that AI brings to life. The article highlights a number of problems and challenges for Russian industry based on the results of applied research conducted in November-December 2023 at 18 medium and large industrial enterprises. The main conclusions include not only the identified systemic problems and risks (shortcomings in digitalisation methodology, ambiguity in calculating economic parameters, lack of technical expertise), but also the most promising areas for the development of AI technologies. The study finds significant potential for enhancing the technologies of the Industry 3.0 and Industry 4.0 paradigms using AI tools. Also, it describe the necessary changes in enterprise management and regulatory government activities aimed at realising the identified potential. In conclusion, the article emphasises the need to optimise parallel imports, develop human capital and adequately analyse the economic parameters of industrial enterprises’ digital transformation project. The authors emphasise the relevance of studying the prospects for the development of AI in industry for Russian economic science in the period 2024–2026.
ISSN:2220-6469
2220-7872