The impact of brand inclusivity on consumer attitudes toward AI-designed products

Chunqu Xiao et al.

Asia Pacific Journal of Marketing and Logistics2026https://doi.org/10.1108/apjml-10-2025-2139article
AJG 1ABDC A
Weight
0.50

Abstract

Purpose As the use of artificial intelligence (AI) in product design becomes increasingly prevalent, consumer resistance to AI-designed products has become a pressing challenge in brand management. Although existing research has explored consumers’ negative reactions from the perspective of algorithm aversion, limited attention has been given to the antecedents that enhance consumer evaluations of AI-designed products. In response to this gap, the present study focuses on the concept of brand inclusivity, which refers to a brand’s openness to and acceptance of diverse agents and creators, and examines whether and how it influences consumer attitudes toward AI-designed products. Design/methodology/approach Four online experiments were conducted to examine the effect of brand inclusivity on consumers’ attitudes toward AI-designed products. The hypotheses were tested using statistical analyses, including t-tests, ANOVAs, and regression analyses. Findings Consumers evaluate AI-designed products more favorably when they are offered by high-inclusivity brands, an effect mediated by increased perceived consistency. This positive effect diminishes when the brand offers hedonic products that conflict with the use of AI design, or when the AI designer is perceived as a tool rather than an anthropomorphic entity. Originality/value Findings extend understanding of how to mitigate research on brand inclusivity’s downstream effects, and advance the conceptualization of AI’s social role as a designer. The results provide practical guidance for promoting AI-driven product design and implementing inclusive marketing strategies.algorithm aversion, enrich.

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https://doi.org/https://doi.org/10.1108/apjml-10-2025-2139

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@article{chunqu2026,
  title        = {{The impact of brand inclusivity on consumer attitudes toward AI-designed products}},
  author       = {Chunqu Xiao et al.},
  journal      = {Asia Pacific Journal of Marketing and Logistics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/apjml-10-2025-2139},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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