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AI-Driven Personalization in Digital Marketing: Balancing Innovation and Consumer Privacy

by Anna Tanyaradzwa Audrey Chingono, Chipo Talitakhumi Chakweza, Ruvimbo Salome Kanyongo, Rethabile Tlou
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 75
Year of Publication: 2026
Authors: Anna Tanyaradzwa Audrey Chingono, Chipo Talitakhumi Chakweza, Ruvimbo Salome Kanyongo, Rethabile Tlou
10.5120/ijca2026926297

Anna Tanyaradzwa Audrey Chingono, Chipo Talitakhumi Chakweza, Ruvimbo Salome Kanyongo, Rethabile Tlou . AI-Driven Personalization in Digital Marketing: Balancing Innovation and Consumer Privacy. International Journal of Computer Applications. 187, 75 ( Jan 2026), 68-85. DOI=10.5120/ijca2026926297

@article{ 10.5120/ijca2026926297,
author = { Anna Tanyaradzwa Audrey Chingono, Chipo Talitakhumi Chakweza, Ruvimbo Salome Kanyongo, Rethabile Tlou },
title = { AI-Driven Personalization in Digital Marketing: Balancing Innovation and Consumer Privacy },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2026 },
volume = { 187 },
number = { 75 },
month = { Jan },
year = { 2026 },
issn = { 0975-8887 },
pages = { 68-85 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number75/ai-driven-personalisation-in-digital-marketing-balancing-innovation-and-consumer-privacy/ },
doi = { 10.5120/ijca2026926297 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-01-20T22:56:31.186754+05:30
%A Anna Tanyaradzwa Audrey Chingono
%A Chipo Talitakhumi Chakweza
%A Ruvimbo Salome Kanyongo
%A Rethabile Tlou
%T AI-Driven Personalization in Digital Marketing: Balancing Innovation and Consumer Privacy
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 75
%P 68-85
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial intelligence (AI)-driven personalisation is reshaping digital marketing by enabling hyper-targeted experiences, but it also intensifies privacy concerns and ethical dilemmas. This systematic review examines the interaction between AI-enabled marketing and consumer trust, algorithmic transparency, and ethical governance, drawing on 41 peer-reviewed studies published between 2014 and 2025. The review employs thematic synthesis to extract five key thematic domains: the trust-personalisation paradox, explainability in AI systems, ethical governance, consumer empowerment, and future research trajectories. Findings reveal that although AI personalisation enhances engagement and perceived relevance, it often lacks transparent mechanisms and clear ethical boundaries, thereby eroding user trust. Empirical evidence suggests that permission-based targeting, explainable AI, and consumer-controlled data frameworks are emerging as best practices, although they are rarely adopted systematically. Gaps remain in the operationalisation of ethical AI, particularly across cultural contexts and long-term behavioural outcomes. The review concludes that ethical AI marketing must prioritise user empowerment, institutionalise transparency, and position ethical governance as a strategic asset in digital engagement.

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Index Terms

Computer Science
Information Sciences

Keywords

AI Personalisation Predictive Analytics Algorithmic Transparency Federated Learning Consumer Trust

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