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How Perceptions Variance Shapes Brand Culture: Deconstructing Consumer Cognition Through a Comparison of Generative AI and Human-generated Texts

Ziye Li, Qian Dong
Vol. 7, No. 1, pp. 42-51, 2026 DOI: 10.54097/p7p3gb13 April 30, 2026
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Abstract.This study investigated how differences in consumer perceptions of content origin—specifically between Gen-AI and human creation—influence brand culture, with a focus on addressing the underexplored connection between content authorship and brand cultural formation. Drawing on the Elaboration Likelihood Model (ELM), brand signal theory, and cultural consistency theory, two empirical studies were carried out to unpack the cognitive and affective mechanisms underlying this relationship. Study 1 compared consumer perceptions across four dimensions—brand authenticity, credibility, electronic word-of-mouth (EWOM) intentions, and brand attitudes. Findings indicated no significant differences in these perceptions between the two AI tools. Study 2 further explored the impact of human-generated versus DeepSeek-generated texts on brand culture. Results revealed that human-authored narratives significantly outperformed AI-generated content in enhancing perceptions of authenticity, credibility, EWOM intentions, brand attitudes, and brand culture. Brand credibility is the only factor with a significant positive effect on brand culture. Additionally, text origin (human vs. AI) played a moderating role, with human authorship strengthening the resonance between perceptual dimensions and brand culture. The AI origin functions as a negative peripheral cue under the ELM framework triggered heuristic skepticism. The study offered practical insights for marketers on integrating Gen-AI into brand communication while preserving cultural coherence.
Keywords. Generative AI human-generated text brand culture consumer perception csultural consistency
APA Citation Ziye Li, Qian Dong (2026). How Perceptions Variance Shapes Brand Culture: Deconstructing Consumer Cognition Through a Comparison of Generative AI and Human-generated Texts. Journal of Computer Science and Artificial Intelligence, 7(1), 42-51. https://doi.org/10.54097/p7p3gb13

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