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Strategizing: Theory and Practice
UDC 35

STRATEGIC SCENARIOS FOR ARTIFICIAL INTELLIGENCE IN MARKETING Strategic Scenarios for Artificial Intelligence in Marketing

Published in Strategizing: Theory and Practice · Volume 6, Issue 4, 2026 · Pages 559–574 · Rubric: Innovative Development Strategies
DOI: https://doi.org/10.21603/2782-2435-2026-6-4-559-574 · EDN: SAAVGS
Received: 11.01.2026 Accepted: 08.04.2026 Published: 27.10.2026 Language of publication: RUS
Authors
VL
Vladislav Shadrin
ORCID
ABSTRACT
Modern marketing is deeply integrated with artificial intelligence, which radically transforms traditional marketing patterns. The authors used Professor Vladimir L. Kvint’s methodology of strategizing to analyze the evolution of AI in marketing and identify its current strategic priorities amidst digital transformation. The theory of strategy and the strategizing methodology enable companies to cultivate long-term competitive advantages and mitigate risks in an uncertain environment. This approach prioritizes stakeholder values, interests, and competitive advantages. It employs scenario-based forecasting in an uncertain environment. Statistical data analysis, a review of corporate strategies, and case studies made it possible to identify four historical waves of AI development in marketing, ranging from early personalization to generative models. Russia is accelerating its AI applications with a strategic focus on technological independence. AI in marketing is used for hyper-personalization, content generation, and predictive analytics, which are associated with ethical and reputational risks. The optimal scenarios for strategic development involve a managed integration approach that balances automation with human oversight. Integrating AI into marketing should prioritize the values of businesses and consumers over technical capabilities. An effective combination of technological innovation with human capital may eventually ensure sustainable development in the sector.
KEYWORDS
marketing, artificial intelligence (AI), strategizing, Vladimir Kvint’s methodology of strategizing, strategic choice, digital transformation, risks, strategic values
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1. Vlasyuk GV, Gruzdeva SE. Konkurentosposobnost’ predlozheniya kak faktor konkurentosposobnosti organizacii [Competitiveness of the offer as a factor of competitiveness of the organization]. Trendy` i upravlenie [Trends and Management]. 2014;(1):63–73. (In Russ.) https://doi.org/10.7256/2307-9118.2014.1.12276

2. Germanchuk AN, Mizyaeva NO. Artificial intelligence in marketing: New opportunities and challenges of digital transformation. Vestnik of Donetsk University. Series 03. Economics and Law. 2024;(4):15–22. (In Russ.) https://doi.org/10.5281/zenodo.14554098

3. Deynekin TV. Iskusstvennyy intellekt v marketinge [Artificial intelligence in marketing]. Marketing in Russia and Abroad. 2019;(2):33–38. (In Russ.) https://elibrary.ru/ZBZPZZ

4. Kvint VL. The concept of strategizing. Vol. 2. St. Petersburg: NWIM RANEPA; 2020. 164 p. (In Russ.) https://elibrary.ru/XGGPYG

5. Kvint VL, Khvorostyanaya AS, Sasaev NI. Advanced technologies in strategizing. Economics and Management. 2020;26(11):1170–1179. (In Russ.) https://doi.org/10.35854/1998-1627-2020-11-1170-1179

6. Neganov SA. Artificial intelligence in marketing: A balanced approach to opportunities and risks. Bulletin of the Academy of Knowledge. 2025;(2):1119–1122. (In Russ.) https://elibrary.ru/PCNBDU

7. Petrova PM. Strategic management during the contingency period in the regional real estate market. Administrative Consulting. 2022;(9):151–162. (In Russ.) https://doi.org/10.22394/1726-1139-2022-9-151-162

8. Sadovnichaya AV. Social and economic efficiency of exhibitions and fairs: Methodology and practice. E`konomicheskoe vozrozhdenie Rossii [Russia's Economic Revival]. 2019;(1):76–85. (In Russ.) https://elibrary.ru/YYIUMX

9. Khvorostyanaya AS. Transforming the strategic communications system in the light industry and fashion. Strategizing: Theory and Practice. 2024;4(1):85–95. (In Russ.) https://doi.org/10.21603/2782-2435-2024-4-1-85-95

10. Chkhotua IZ, Khvorostyanaya AS. Strategic priorities of developing a communication strategy for a tourist brand. Russian Journal of Industrial Economics. 2021;14(2):172–183. (In Russ.) https://doi.org/10.17073/2072-1633-2021-2-172-183

11. Haleem A, Javaid M, Qadri MA, Singh RP, Suman R. Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks. 2022;3:119–132. https://doi.org/10.1016/j.ijin.2022.08.005

12. Stone M, Aravopoulou E, Ekinci Y, Evans G, Hobbs M, et al. Artificial intelligence (AI) in strategic marketing decision-making: A research agenda. The Bottom Line. 2020;33(2):183–200. https://doi.org/10.1108/BL-03-2020-0022

13. Mustak M, Salminen J, Plé L, Wirtz J. Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research. 2021;124:389–404. https://doi.org/10.1016/j.jbusres.2020.10.044

14. Davenport TH, Ronanki R. Artificial intelligence for the real world. Harvard business. 2018;96(1):108–116.

15. Huang MH, Rust RT. A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science. 2021;49:30–50. https://doi.org/10.1007/s11747-020-00749-9

16. Kaplan A, Haenlein M. Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons. 2019;62(1):15–25. https://doi.org/10.1016/j.bushor.2018.08.004

17. Kumar V, Ashraf AR, Nadeem W. AI-powered marketing: What, where, and how? International Journal of Information Management. 2024;77:102783. https://doi.org/10.1016/j.ijinfomgt.2024.102783

18. Labib E. Artificial intelligence in marketing: Exploring current and future trends. Cogent Business & Management. 2024;11(1):2348728. https://doi.org/10.1080/23311975.2024.2348728

19. Madanchian M. The impact of artificial intelligence marketing on E-commerce sales. Systems. 2024;12(10):429. https://doi.org/10.3390/systems12100429

20. Saura JR, Škare V, Dosen DO. Is AI-based digital marketing ethical? Assessing a new data privacy paradox. Journal of Innovation & Knowledge. 2024;9(4):100597. https://doi.org/10.1016/j.jik.2024.100597

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Vladimir Kvint
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Vladimir Kvint
vlkvint@gmail.com
Albert Bakhtizin
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Albert Bakhtizin
albert.bakhtizin@gmail.com
Anna Khvorostyanaya
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Anna Khvorostyanaya
Khvorostyanayaas@gmail.com
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