Modern Directions of Artificial Intelligence Development and Its Application in an Organization’s Marketing Activities
Rozhko V. I., Yevdunov I. M.

Rozhko, Viktor I., and Yevdunov, Illia M. (2025) “Modern Directions of Artificial Intelligence Development and Its Application in an Organization’s Marketing Activities.” The Problems of Economy 4:246–253.
https://doi.org/10.32983/2222-0712-2025-4-246-253

Section: Economics and Enterprise Management

UDC 339.138:004.8

Abstract:
The article examines current trends in the development of artificial intelligence technologies and analyzes their practical application in the marketing activities of organizations. The relevance of the study is driven by the rapid development of digital technologies, the projected growth of the global AI market in marketing to USD 107.5 billion by 2028, and the need to adapt marketing strategies to new business conditions in the era of the Fourth Industrial Revolution. The aim of the article is to explore the current directions of artificial intelligence development and to systematize approaches to its application in organizations’ marketing activities. In the course of the research, methods of analysis and synthesis were used to study the theoretical foundations of artificial intelligence and marketing activities, the method of systematization was applied to organize AI tools according to marketing functional areas, comparative analysis was employed to identify the advantages and challenges of implementing AI technologies, the tabular method was used to visually present the results, and the generalization method was used to formulate conclusions. The information base consists of scientific works published in leading professional journals and analytical reports from consulting firms. The key areas of AI technology development have been identified: machine learning, deep learning, natural language processing, computer vision, and generative artificial intelligence. The advantages of using intelligent systems in marketing have been characterized: increasing targeting efficiency by 30–50%, boosting conversion by 15–30%, reducing content creation time by 60–80%, and lowering customer acquisition costs by 20–40%. A systematization of the main artificial intelligence tools was carried out across six functional areas of marketing: consumer analysis, personalization, content marketing, advertising campaigns, customer service, analytics, and forecasting. The prospects for further development of AI technologies in the context of marketing digitalization are substantiated: deeper integration of various technologies, development of Edge AI and federated learning, improvement of generative models, implementation of explainable AI, and development of agent systems. The practical significance of the results lies in their potential use for forming strategies to implement artificial intelligence in the marketing activities of organizations across different economic sectors and scales.

Keywords: artificial intelligence, marketing, digital transformation, machine learning, personalization, marketing automation, generative AI.

Tabl.: 3. Bibl.: 16.

Rozhko Viktor I. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Marketing, Management and Entrepreneurship, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine)
Email: viktor.rozhko@karazin.ua
Yevdunov Illia M. – Masters Student, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine)
Email: illya.evdunov@gmail.com

List of references in article

Campbell C., Sands S., Ferraro C., Tsao H.-Y. & Mavrommatis A. (2020). From data to action: How marketers can leverage AI. Business Horizons, 2(63), 227–243. https://doi.org/10.1016/j.bushor.2019.12.002
Chui M., Manyika J. & Miremadi M. (2023). Where machines could replace humans—and where they can't (yet). McKinsey Quarterly. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights
Davenport T., Guha A., Grewal D. & Bressgott T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24–42. https://doi.org/10.1007/s11747-019-00696-0
De Bruyn A., Viswanathan V., Beh Y. S., Brock J. K.-U. & von Wangenheim F. (2020). Artificial Intelligence and Marketing: Pitfalls and Opportunities. Journal of Interactive Marketing, 51, 91–105. https://doi.org/10.1016/j.intmar.2020.04.007
Epsilon Research. (2023). The Power of Me: The Impact of Personalization on Marketing Performance. https://www.epsilon.com/us/insights
Gartner Research. (2024). Top Strategic Technology Trends for 2024. https://www.gartner.com/en/articles/gartner-top-10-strategic-technology-trends-for-2024
Grand View Research. (2021). Artificial Intelligence In Marketing Market Size Report, 2021-2028. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-marketing-market
Huang M.-H. & Rust R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 2(21), 155–172. https://doi.org/10.1177/1094670517752459
Iliashenko S. M. & Ivanova T. Ye. (2021). Perspektyvy tsyfrovizatsii marketynhovoi diialnosti ukrainskykh pidpryiemstv [Prospects for digitalization of marketing activities of Ukrainian enterprises]. Marketynh i tsyfrovi tekhnolohii, 1(5), 28–45. https://doi.org/10.15276/mdt.5.1.2021.3
Kravchenko V. A. (2022). Vprovadzhennia shtuchnoho intelektu v biznes-protsesy ukrainskykh kompanii: mozhlyvosti ta obmezhennia [Implementation of artificial intelligence in business processes of Ukrainian companies: opportunities and limitations]. Infrastruktura rynku, 65, 112–118. https://doi.org/10.32843/infrastruct65-19
Kumar V., Rajan B., Venkatesan R. & Lecinski J. (2019). Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing. California Management Review, 4(61), 135–155. https://doi.org/10.1177/0008125619859317
Oklander M. A. & Romanenko O. O. (2020). Tsyfrovi tekhnolohii v marketynhu: virtualna i dopovnena realnist [Digital technologies in marketing: virtual and augmented reality]. Ekonomichnyi visnyk Natsionalnoho tekhnichnoho universytetu Ukrainy «Kyivskyi politekhnichnyi instytut», 17, 63–73. https://doi.org/10.20535/2307-5651.17.2020.216367
Provost F. & Fawcett T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. Sebastopol: O'Reilly Media.
Russell S. & Norvig P. (2021). Artificial Intelligence: A Modern Approach. Hoboken: Pearson.
Salesforce Research. (2024). State of Marketing Report 2024. https://www.salesforce.com/resources/research-reports/state-of-marketing/
Syam N. & Sharma A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management, 69, 135–146. https://doi.org/10.1016/j.indmarman.2017.12.019