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Artificial Intelligence-Enabled Digital Marketing: Applications, Customer Value, Ethical Risks and A Research Agenda
Subject area: Arts, Social Sciences and Humanities · Area of research: Artificial Intelligence-Enabled Digital Marketing
Abstract
Artificial intelligence (AI) has moved from an experimental technology to a strategic capability in digital marketing. Machine learning, natural language processing, recommendation systems, conversational agents, computer vision, predictive analytics and generative AI are increasingly embedded in customer acquisition, segmentation, content creation, advertising, service and retention. This paper develops a structured review of recent literature on AI-enabled digital marketing, with emphasis on applications, customer value, organizational benefits, ethical risks and emerging research needs. Literature published primarily during 2020–2026 was examined through a structured thematic synthesis, supported by influential earlier studies that established the conceptual foundations of AI in marketing. The review indicates that AI creates value through personalization, predictive decision-making, automation, real-time customer interaction and improved marketing intelligence. At the same time, algorithmic bias, privacy risks, opacity, misinformation, over-automation and declining consumer trust can weaken the value created by AI. The paper proposes an integrated framework in which AI capability influences digital marketing performance through customer experience and marketing decision quality, while data governance, transparency, human oversight and organizational readiness act as boundary conditions. The study contributes a practical and research-oriented agenda for responsible AI adoption in digital marketing, particularly in emerging-market contexts such as India.
Keywords
Artificial intelligence, customer experience, digital marketing, generative AI, marketing analytics, personalization, responsible AI.
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How to cite this paper
@article{1722950,
author = {V. Lathika, J. Jerin Sofia},
title = {Artificial Intelligence-Enabled Digital Marketing: Applications, Customer Value, Ethical Risks and A Research Agenda},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {1603-1610},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1722950.pdf},
abstract = {Artificial intelligence (AI) has moved from an experimental technology to a strategic capability in digital marketing. Machine learning, natural language processing, recommendation systems, conversational agents, computer vision, predictive analytics and generative AI are increasingly embedded in customer acquisition, segmentation, content creation, advertising, service and retention. This paper develops a structured review of recent literature on AI-enabled digital marketing, with emphasis on applications, customer value, organizational benefits, ethical risks and emerging research needs. Literature published primarily during 2020–2026 was examined through a structured thematic synthesis, supported by influential earlier studies that established the conceptual foundations of AI in marketing. The review indicates that AI creates value through personalization, predictive decision-making, automation, real-time customer interaction and improved marketing intelligence. At the same time, algorithmic bias, privacy risks, opacity, misinformation, over-automation and declining consumer trust can weaken the value created by AI. The paper proposes an integrated framework in which AI capability influences digital marketing performance through customer experience and marketing decision quality, while data governance, transparency, human oversight and organizational readiness act as boundary conditions. The study contributes a practical and research-oriented agenda for responsible AI adoption in digital marketing, particularly in emerging-market contexts such as India.},
keywords = {Artificial intelligence, customer experience, digital marketing, generative AI, marketing analytics, personalization, responsible AI.},
month = {September},
}