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Paper ID:IJSREM67273

ROLE OF ARTIFICIAL INTELLIGENCE IN DIGITAL MARKETING AND CUSTOMER ENGAGEMENT

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67273

Volume:

10 |

9 |

Sep 2026

Pages:

1-19

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM67273

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AS

Alyaan Siddique

School of sciences (BCA)

KK Modi University Durg

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DMBA

Dr. Mohammed Bakhtawar Ahmed

School of sciences (BCA)

KK Modi University Durg

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Abstract

Artificial intelligence (AI) has moved from an experimental technology to a core digital marketing capability. Modern marketing systems use machine learning, natural language processing, recommender systems, generative AI, sentiment analysis, predictive analytics, and automation to influence how firms understand customers, create content, personalize offers, communicate in real time, and evaluate campaign performance. This paper examines the role of AI in digital marketing and customer engagement through a structured literature-based analysis of recent and foundational research published from 2019 to 2026. The review synthesizes evidence concerning AI-enabled personalization, conversational interfaces, content generation, predictive decision-making, social media marketing, and customer-experience management. The analysis shows that AI can strengthen engagement by improving relevance, speed, convenience, responsiveness, and perceived value. However, the literature also demonstrates that technological capability alone does not guarantee positive engagement. Privacy concerns, algorithmic bias, lack of transparency, inaccurate generated content, perceived loss of human connection, and inappropriate automation can reduce trust and weaken relationships. The paper therefore proposes a conceptual framework in which AI marketing capabilities influence customer engagement through customer-perceived value, trust, and experience, while AI disclosure, customer expertise, task complexity, and channel context act as boundary conditions. The study concludes with managerial implications and a future research agenda focused on responsible personalization, human-AI collaboration, disclosure practices, measurable engagement outcomes, and context-sensitive AI adoption.

KEYWORDS

Artificial intelligence digital marketing customer engagement personalization generative AI chatbots predictive analytics customer experience trust.

Cite This Article

Alyaan Siddique, Dr. Mohammed Bakhtawar Ahmed, "ROLE OF ARTIFICIAL INTELLIGENCE IN DIGITAL MARKETING AND CUSTOMER ENGAGEMENT," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 9, pp. 1-19, Sep 2026. https://doi.org/10.55041/IJSREM67273

Full Article/Conclusion

Artificial intelligence is reshaping digital marketing by changing how firms identify customer needs, personalize communication, generate content, automate interactions, and make decisions. The literature reviewed in this paper indicates that AI can increase customer engagement when it creates meaningful value through relevance, convenience, responsiveness, enjoyment, and reliability. However, the same technologies can reduce engagement when customers experience privacy intrusion, opacity, bias, inaccurate content, or loss of human connection. The central conclusion is therefore not that more AI automatically produces better marketing. Instead, effective AI marketing depends on matching technology to customer needs, preserving appropriate human involvement, and designing transparency and governance into the experience. The proposed framework positions perceived value, trust, and customer experience as key mechanisms linking AI capabilities with engagement, while disclosure, expertise, complexity, and channel context shape the strength of those relationships. This framework can support future empirical studies and provide managers with a structured way to evaluate AI initiatives beyond short-term campaign efficiency.

References

[1] T. H. Davenport, A. Guha, D. Grewal, and T. Bressgott, “How artificial intelligence will change the future of marketing,” Journal of the Academy of Marketing Science, vol. 48, pp. 24–42, 2020, doi: 10.1007/s11747-019-00696-0. [2] D. Grewal, C. B. Satornino, T. Davenport, A. Guha, E. Haenlein, A. K. Gupta, and M. Wetzstein, “How generative AI is shaping the future of marketing,” Journal of the Academy of Marketing Science, vol. 53, pp. 702–722, 2025, doi: 10.1007/s11747-024-01064-3. [3] H. Borimnejad and V. Borimnejad, “Emerging trends challenges and research opportunities in artificial intelligence applications in marketing,” Discover Artificial Intelligence, vol. 6, art. no. 9, 2026, doi: 10.1007/s44163-025-00705-y. [4] M. R. M. Amin, A. Asbi, V. M. Sivakumaran, J. Kim, and E. Septiarini, “Artificial intelligence (AI) adoption in marketing strategies: Navigating the present and shaping the future business landscape,” Social Sciences & Humanities Open, vol. 12, art. no. 102048, 2025, doi: 10.1016/j.ssaho.2025.102048. [5] S. Joshi, S. Bhattacharya, P. Pathak, N. A. Natraj, J. Saini, and S. Goswami, “Harnessing the potential of generative AI in digital marketing using the Behavioral Reasoning Theory approach,” International Journal of Information Management Data Insights, vol. 5, no. 1, art. no. 100317, 2025, doi: 10.1016/j.jjimei.2024.100317. [6] Y. Liu-Thompkins, S. Okazaki, and H. Li, “Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience,” Journal of the Academy of Marketing Science, vol. 50, pp. 1198–1218, 2022, doi: 10.1007/s11747-022-00892-5. [7] “Factors affecting customer engagement in AI marketing,” Telematics and Informatics Reports, vol. 19, art. no. 100230, 2025, doi: 10.1016/j.teler.2025.100230. [8] L. Hollebeek, R. Sprott, and M. Brady, “Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research,” Psychology & Marketing, vol. 41, no. 4, pp. 880–898, 2024, doi: 10.1002/mar.21957. [9] M. H. Huang and R. T. Rust, “A strategic framework for artificial intelligence in marketing,” Journal of the Academy of Marketing Science, vol. 49, pp. 30–50, 2021, doi: 10.1007/s11747-020-00749-9. [10] P. K. Kopalle, M. Gangwar, A. Kaplan, D. Ramachandran, W. Reinartz, and A. Rindfleisch, “Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities,” International Journal of Research in Marketing, vol. 39, no. 2, pp. 522–540, 2022, doi: 10.1016/j.ijresmar.2021.11.002.

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Publication Date

9/15/2026

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