IDEAS home Printed from https://ideas.repec.org/p/zbw/esconf/343411.html

Artificial Intelligence in Marketing: Trends, Opportunities and Challenges

Author

Listed:
  • Vujinović, Sofija
  • Lazarević, Marija

Abstract

The rapid development and application of artificial intelligence (AI) are transforming marketing practices and altering the way companies engage with customers. The changes are multifaceted and are reflected in improved message personalization, optimization of communication channels, detailed data analysis, and enhanced customer experience. The aim of this research is to analyze the role and significance of AI in contemporary marketing communications, with a special focus on how it transforms the approach, form, and effectiveness of communication between companies and consumers. The paper is based on a literature review and reports, with a particular focus on the latest research on the application of AI in marketing. Sources were selected based on relevance and timeliness, and the analysis was conducted through systematization and interpretation of key trends. The findings are discussed in the context of the existing literature and practical implications for the use of artificial intelligence in marketing. The findings suggest that AI in marketing is not only a technical tool but also a strategic resource for sustainable competitiveness and digital transformation acceleration, with its adoption in organizations continuously increasing. This reveals the need for further research and careful application of AI tools in business practice, as well as the alignment of educational and development policy to meet the needs of the digital economy.

Suggested Citation

  • Vujinović, Sofija & Lazarević, Marija, 2025. "Artificial Intelligence in Marketing: Trends, Opportunities and Challenges," EconStor Conference Papers 343411, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esconf:343411
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/343411/1/ABS28-Corrected.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    2. Agustí Segarra-Blasco & Josep Tomàs-Porres & Mercedes Teruel, 2025. "AI, robots and innovation in European SMEs," Small Business Economics, Springer, vol. 65(1), pages 719-745, June.
    3. Shahriar Akter & Saida Sultana & Marcello Mariani & Samuel Fosso Wamba & Konstantina Spanaki & Yogesh Dwivedi, 2023. "Advancing algorithmic bias management capabilities in AI-driven marketing analytics research," Post-Print hal-04194438, HAL.
    4. Michael Haenlein & Ming-Hui Huang & Andreas Kaplan, 2022. "Guest Editorial: Business Ethics in the Era of Artificial Intelligence," Journal of Business Ethics, Springer, vol. 178(4), pages 867-869, July.
    5. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    6. Kirk, Colleen P. & Givi, Julian, 2025. "The AI-authorship effect: Understanding authenticity, moral disgust, and consumer responses to AI-generated marketing communications," Journal of Business Research, Elsevier, vol. 186(C).
    7. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Satornino, Cinthia B. & Grewal, Dhruv & Guha, Abhijit & Schweiger, Elisa B. & Goodstein, Ronald C., 2023. "The perks and perils of artificial intelligence use in lateral exchange markets," Journal of Business Research, Elsevier, vol. 158(C).
    2. Zobair, Alwia Saeed Osman & Kodai, Zainab Mohammed Osman & Almansour, Mohammed Abdulaziz & Mohammed, Salwa Dirar Awad & Agag, Gomaa & Alipour, Osman, 2026. "When AI advice backfires: Field experimental evidence on personalization, intrusiveness, and purchase behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 92(C).
    3. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    4. Robertson, Jeandri & Botha, Elsamari & Oosthuizen, Kim & Montecchi, Matteo, 2025. "Managing change when integrating artificial intelligence (AI) into the retail value chain: The AI implementation compass," Journal of Business Research, Elsevier, vol. 189(C).
    5. Abhijit Guha & Dhruv Grewal, 2022. "How robots will affect the future of retailing," AMS Review, Springer;Academy of Marketing Science, vol. 12(3), pages 245-252, December.
    6. Qin, Min & Qiu, Shanshan & Mou, Jian, 2025. "Task supported or task decision-making? Which AI workplace enhances employee AI identity more in manufacturing enterprise," Technology in Society, Elsevier, vol. 83(C).
    7. Van Kien Pham & Thuy Dung Pham Thi & Nam Tien Duong, 2024. "A Study on Information Search Behavior Using AI-Powered Engines: Evidence From Chatbots on Online Shopping Platforms," SAGE Open, , vol. 14(4), pages 21582440241, November.
    8. Vincent Charles & Nripendra P. Rana & Ilias O. Pappas & Morten Kamphaug & Keng Siau & Kenth Engø-Monsen, 2024. "The Next ‘Deep’ Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach," Information Systems Frontiers, Springer, vol. 26(3), pages 851-856, June.
    9. Secretaria, Norberto M., 2026. "Trust in AI-Driven Marketing and its Impact on Brand Loyalty: The Mediating Role of Adoption Intention among Generation Z Consumers," International Review of Management and Marketing, International Review of Management and Marketing, vol. 16(3), pages 566-574, March.
    10. Pantano, Eleonora & Viassone, Milena & Boardman, Rosy & Dennis, Charles, 2022. "Inclusive or exclusive? Investigating how retail technology can reduce old consumers’ barriers to shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    11. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    12. Jifeng Mu & Jonathan Z. Zhang, 2025. "Artificial intelligence marketing usage and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 53(4), pages 1081-1134, July.
    13. Audrin, Bertrand & Etemad-Sajadi, Reza, 2026. "The impact of self-service technologies on consumer-retailer relationships: navigating trust, contribution, and the role of consumers as partial employees," Journal of Business Research, Elsevier, vol. 207(C).
    14. Dr. Suby Baby & Dr Priya Mariyat, 2026. "Artificial Intelligence-Driven Commerce: Consumer Trust, Adoption Behaviour and Firm Performance a Mixed-Methods Investigation Across Emerging and Developed Markets," International Journal of Research and Innovation in Applied Science, RSIS International, vol. 11(6), pages 400-409, June.
    15. Chenfeng Yan & Quan Chen & Xinyue Zhou & Xin Dai & Zhilin Yang, 2024. "When the Automated fire Backfires: The Adoption of Algorithm-based HR Decision-making Could Induce Consumer’s Unfavorable Ethicality Inferences of the Company," Journal of Business Ethics, Springer, vol. 190(4), pages 841-859, April.
    16. Li, Sixian & Peluso, Alessandro M. & Duan, Jinyun, 2023. "Why do we prefer humans to artificial intelligence in telemarketing? A mind perception explanation," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    17. El-Manstrly, Dahlia & Herhausen, Dennis & Guha, Abhijit & Blut, Markus & Grewal, Dhruv, 2024. "Should online retailers emphasize efficiency or experience? First insights on the evolution and heterogeneity of website attributes," Journal of Retailing, Elsevier, vol. 100(2), pages 274-292.
    18. Grewal, Dhruv & Benoit, Sabine & Noble, Stephanie M. & Guha, Abhijit & Ahlbom, Carl-Philip & Nordfält, Jens, 2023. "Leveraging In-Store Technology and AI: Increasing Customer and Employee Efficiency and Enhancing their Experiences," Journal of Retailing, Elsevier, vol. 99(4), pages 487-504.
    19. Sreedhar Madhavaram & Radha Appan, 2024. "AI for marketing: Enabler? Engager? Ersatz?," AMS Review, Springer;Academy of Marketing Science, vol. 14(3), pages 258-277, December.
    20. Alabed, Amani & Javornik, Ana & Gregory-Smith, Diana, 2022. "AI anthropomorphism and its effect on users' self-congruence and self–AI integration: A theoretical framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M39 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Other
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:esconf:343411. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.