AI-Driven Marketing in the Digital Era: Personalization, Customer Engagement and the Transformation of Consumer Behaviour

Volume 11, Issue 3, 2026

International Journal of Commerce and Management Studies, ISSN 2456-3684

Paper Title

Author Name and Affiliation

Dr. V. Srividhya

Associate Professor in Commerce, Government First Grade College, Channapatna, Bangalore South District, Karnataka

Email: srividhya0510@gmail.com

Abstract

Artificial Intelligence (AI) has moved from an emerging analytical technology to a strategic component of contemporary marketing. Machine learning, predictive analytics, recommendation systems, natural language processing and generative AI allow firms to interpret large volumes of customer information, automate marketing activities and deliver more context-sensitive interactions. This conceptual paper examines how AI-driven marketing influences personalization, customer experience, customer engagement and consumer behavioural outcomes, while also considering the boundary conditions created by trust, perceived value, privacy concerns, transparency and human oversight. To address the conceptual nature of the study, a structured integrative literature review was undertaken using recent peer-reviewed and scholarly sources, with particular attention to studies published from 2022 to 2026. The review indicates that AI can improve relevance, responsiveness and analytical capability, but the effects are not uniformly positive. Recent research highlights the importance of trust, perceived usefulness, transparency, authenticity and privacy in determining whether consumers accept AI-mediated marketing interactions. Building on these findings, the paper proposes an integrated conceptual framework in which AI marketing capabilities influence consumer behavioural outcomes directly and indirectly through AI-enabled personalization, customer experience and customer engagement. Consumer trust and perceived value are positioned as positive boundary conditions, whereas privacy concerns are positioned as a negative boundary condition; transparency and human oversight are identified as governance mechanisms that can strengthen responsible implementation. The paper contributes by integrating the technology, consumer and governance dimensions of AI-driven marketing into one conceptual model and by identifying testable propositions for future empirical research. The study also provides practical recommendations concerning data governance, explainability, personalization controls, human-AI collaboration, employee capability development and continuous performance monitoring.

Keywords

Artificial Intelligence, AI-Driven Marketing, Personalization, Customer Engagement, Customer Experience, Consumer Behaviour, Consumer Trust, Generative AI, Privacy, Transparency

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DOI

DOI: https://doi.org/10.67061/ijcams.2026.vol.11.issue.03.8127

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