Features of using artificial intelligence in companies’marketing communications

Author:

Arzhanova K. A.1ORCID,Pisklakova L. D.1ORCID

Affiliation:

1. State University of Management

Abstract

The use of artificial intelligence (hereinafter referred to as Al) is one of the leading trends in marketing and advertising in recent years. With its help, it is possible to solve tasks of varying complexity: from generating ideas for promotion to creating advertising creatives. The research problem is that in order to work effectively, companies need to understand which neural networks can most optimally solve the tasks of marketing activities. To do this, it is necessary to define a list of such neural networks. The authors consider the use of Al in marketing communications and analyse neural networks that can be used in business. The study purpose is to form a relevant list of neural networks for the implementation of marketing activities of the company. The most popular neural networks, their functionality and features were studied. The domestic and foreign experience analysis of using neural networks in the marketing activities of companies is conducted. Recommendations for more efficient use of neural networks are proposed. Based on the conducted research, a relevant list of neural networks for the implementation of the company’s marketing activities was determined. The methodological basis of the article was formed of publications on the problems of using neural networks in business and marketing sphere. The works of domestic and foreign researchers were studied. The following theoretical research methods were used in the article: analysis, synthesis, problematisation. The content analysis was chosen as an empirical method.

Publisher

State University of Management

Reference20 articles.

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3. Berezhnaya M.N., Rakhmanova E.V., Orlova V.G. Artificial intelligence in modern marketing: tools, opportunities and prospects. In: Strategic planning and enterprise development: Proceedings of the XXIV All-Russian Symposium, Moscow, April 11–12, 2023. Moscow: Central Economic and Mathematical Institute of the Russian Academy of Sciences; 2023. Pp. 21–24. (In Russian).

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