Human Touch in AI Marketing: A Qualitative Synthesis of Brand Authenticity for Generation Z in Indonesia

Desi Derina Yusda; Mochamad Syafii; Restia Christianty

doi:10.61255/jeemba.v4i4.1930

Authors

Desi Derina Yusda Universitas Mitra Indonesia
Mochamad Syafii Universitas Gresik
Restia Christianty Universitas Pattimura

DOI:

https://doi.org/10.61255/jeemba.v4i4.1930

Keywords:

Artificial Intelligence, Human Touch, Brand Authenticity, Generation Z, Qualitative Marketing

Abstract

Purpose – This study examines how Generation Z interprets brand authenticity when marketing communication is created, personalized, or mediated by artificial intelligence (AI), with particular attention to the meaning of human touch. Scope/limitations – Because the evidence is documentary rather than primary consumer testimony, the framework offers analytically transferable propositions for Indonesia, not direct empirical generalization to all Indonesian Generation Z consumers. The component concepts are not claimed as individually new; the contribution lies in their AI-specific configuration, hierarchy, operational indicators, and decision rules.

Methodology– An interpretive qualitative document analysis was conducted using a purposive corpus of peer-reviewed studies and institutional reports on AI marketing, brand authenticity, personalization, virtual influencers, consumer trust, and Generation Z. Evidence was coded through reflexive thematic analysis and constant comparison.

Findings – Five themes explain authentic human touch in AI-based marketing: visible human accountability, relatable imperfection, value congruence, reciprocal empathy, and bounded personalization. Generation Z does not reject AI in principle; authenticity weakens when automation obscures responsibility, removes credible human effort, imitates empathy without escalation, or personalizes beyond acceptable privacy boundaries.

Originality/value – The study develops a Human Touch Authenticity Framework that positions human touch as visible human agency surrounding AI use. The framework explains how brands can combine AI efficiency with transparency, relational responsibility, and value-consistent communication.

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