Stojanović, Danijela and Stojanović, Dijana and Stanisavljević, Nenad (2026) Artificial Intelligence as a Driver of Innovation in Digital Marketing. In: International Conference on Marketing and Technologies: Marketing and smart technologies : proceedings of ICMarkTech 2025. Springer, Charm, pp. 187-199. ISBN 978-3-032-16284-7
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This paper aims to investigate the role and significance of artificial intelligence (AI) in the development and application of digital marketing strategies. Generative AI technologies enable personalized communication with users by creating text, visual, audio, and video content, thereby transforming the creative and analytical dimensions of modern marketing. The study analyzes existing digital marketing strategies and proposes a conceptual framework for integrating generative AI tools—such as ChatGPT, DALL·E, MidJourney, Runway ML, Synthesia, and ElevenLabs—into marketing workflows to enhance visibility, engagement, and efficiency. This research is conceptual in nature and follows a structured literature review within a multi-phase qualitative approach, focused on identifying patterns, benefits, and risks in the application of generative AI in digital marketing. The methodology includes three phases: (1) a review of academic and industry literature, (2) a functional evaluation of selected AI tools, and (3) synthesis of findings into a conceptual model illustrating AI-driven marketing transformation. The results indicate that the adoption of generative AI tools significantly improves the efficiency and personalization of digital marketing campaigns, enhances brand recognition, and fosters stronger user engagement. However, sustainable implementation requires striking a balance between automation and human creativity, while ensuring the ethical and transparent use of AI-generated content. This study contributes to the theoretical understanding of AI integration in marketing and provides practical guidelines for managers on the responsible and effective use of generative technologies. Future research should empirically validate the proposed framework across different industries to assess its broader applicability.
| Item Type: | Book Section |
|---|---|
| Additional Information: | COBISS.ID=193007881 |
| Research Department: | Welfare Economics |
| Depositing User: | Jelena Banovic |
| Date Deposited: | 25 May 2026 07:04 |
| Last Modified: | 25 May 2026 07:04 |
| URI: | http://ebooks.ien.bg.ac.rs/id/eprint/2320 |
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