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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67273
Volume:
10 |
9 |
Sep 2026
Pages:
1-19
Publication Frequency:
Monthly (12 issues per year)
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.
School of sciences (BCA)
KK Modi University Durg
School of sciences (BCA)
KK Modi University Durg
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 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.
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Publication Date
9/15/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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