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Abstract

Objective. The purpose of this article is to explore the potential benefits, challenges, and opportunities of using generative artificial intelligence in marketing and trade. To achieve this goal, it is necessary to analyze current trends in marketing and trade, as well as to identify areas where the use of generative artificial intelligence can have the greatest impact, taking into account the challenges and limitations associated with the implementation of computer linguistics and informatics systems in marketing and trade. Methods. The problems of implementing generative artificial intelligence in the field of marketing and trade are reflected in the works of such researchers as Grazhevska, N, Chyhyrynsky, A, Kraus, N, Holoborodko, O, Popovsky, Y, Proskurnina, N, Steblyuk, N, Kopeykina, E, Hrupovych, S, Borisova T and others. In their research, they identify the most effective artificial intelligence tools in marketing that can help increase the competitiveness and efficiency of a company. Results. Artificial intelligence technologies are developing at a rapid pace. They are becoming increasingly accessible and cost-effective in practical implementation, while providing increasing complexity and speed that far exceeds human capabilities. When analyzing the challenges of using artificial intelligence, it should be noted that it can accelerate growth by providing sales teams with accurate analytics and customer information to effectively identify demand. In addition, artificial intelligence can increase the efficiency and productivity of sales itself by relieving and automating many routine operations to sell the final product and freeing up time to communicate with existing and potential customers. It is important to note that artificial intelligence and generative models provide many opportunities for modern marketing. They help to automate and personalize content, improve the quality of customer interaction, and reduce the time spent on routine tasks. It is considered necessary to strengthen the control and responsibility of companies in the process of creating new roles and competencies in order to ensure the full realization of the existing capabilities of artificial intelligence. Scientific novelty. The scientific novelty of the obtained results is to improve the methodological approach to determining the ways of implementing generative artificial intelligence in marketing and trade in the context of digitalization of the economy. Practical significans. The author's conclusions can be used in the practical activities of domestic enterprises and organizations, as well as form the basis for further digitalization of processes in the production and commercial activities of enterprises. Key words: generative artificial intelligence, machine learning, hyper-personalization, customer experience, customer lifecycle, target audience segmentation, marketing strategies, SEO strategies, personalization, chatbots, marketing effectiveness.