ORIGINAL RESEARCH article
Front. Commun.
Sec. Advertising and Marketing Communication
Volume 10 - 2025 | doi: 10.3389/fcomm.2025.1554551
Gen AI -Gen Z: Understanding Gen Z's Emotional Responses and Brand Experiences with Gen AI-driven, Hyper-personalized Advertising
Provisionally accepted
- 1St Joseph's University, Bengaluru, India
- 2Bath Spa University, Bath, United Kingdom
- 3Christ University, Bangalore, Karnataka, India
- 4Central University of Karnataka, Gulbarga, Karnataka, India
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Gen Z, a tech-savvy consumer group, has highly evolved in its approach to new-age advertising. The rise of Generative Artificial Intelligence (Gen AI) has revolutionized advertising by enabling hyper-personalized content, making it essential to understand its influence on Generation Z (Gen Z) population. This study explores the responses of Gen Z participants in India to Generative Artificial Intelligence based hyper-personalized advertisements, with a specific focus on emotional responses and brand interactions which are significant predictors of advertisement success. Using qualitative research methods, semistructured interviews were conducted with 40 Gen Z participants. Thematic analysis of the data revealed two major themes and five sub-themes: diverse emotional responses, encompassing curiosity and interest as well as fear and suspicion, and enhanced brand experience, encompassing advanced targeted marketing; initial attraction and brand engagement; and brand connection and loyalty, as perceived by the participants Findings imply that brands can harness Gen AI-driven hyper-personalized advertisements to evoke meaningful emotions, enhancing consumer loyalty and building stronger, more personal connections with their audience.
Keywords: Gen AI advertisements, Hyper-personalization, Emotional Responses, Brand interaction, Brand engagement, Brand connection, Brand loyalty
Received: 02 Jan 2025; Accepted: 24 Jun 2025.
Copyright: © 2025 Peter, Roshith, Lawrence, Mona, Narayanan and Yusaira. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Rupa Peter, St Joseph's University, Bengaluru, India
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.