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Consumer attitudes toward AI-generated ads: Appeal types, self-efficacy and AI’s social role

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  • Chen, Yaqi
  • Wang, Haizhong
  • Rao Hill, Sally
  • Li, Binglian

Abstract

While artificial intelligence technology advances have enabled rapid changes in AI generated content (AIGC) in advertising, little is known about consumer attitudes to AI-generated ads. Drawing on mind perception theory, we argue consumers have different attitudes toward AI-generated ads with agentic and communal appeals. Through four experiments, we show that consumers have more positive attitudes toward AI-generated ads with agentic appeals, and the effect is mediated by task self-efficacy, while they have more positive attitudes toward human-created ads with communal appeals, and the effect is mediated by social self-efficacy. Additionally, we found that assigning a social role to the AI advertising generator, a partner or a servant role, helps mitigate or even reverse the negative effects of AI-generated ads with communal appeals. This study contributes to the literature on AI advertising effectiveness, AI as an information source, and advertising appeals and provides meaningful insights and practical guidelines for advertisers.

Suggested Citation

  • Chen, Yaqi & Wang, Haizhong & Rao Hill, Sally & Li, Binglian, 2024. "Consumer attitudes toward AI-generated ads: Appeal types, self-efficacy and AI’s social role," Journal of Business Research, Elsevier, vol. 185(C).
    • Handle: RePEc:eee:jbrese:v:185:y:2024:i:c:s0148296324003710
    DOI: 10.1016/j.jbusres.2024.114867
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    4. Iulia POSTOLACHI & Irina-Constanța THEODORU, 2026. "Embracing Hybrid Intelligence: An Exploratory Study on AI Adoption in Content Creation Among Romanian Marketing Professionals," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, vol. 1(1), pages 7-20, March.
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    7. Hou, Chenxuan & Li, Tingting & Gu, Yanzhang, 2026. "Artificial intelligence versus human providers for personalized solutions? The influence of expected group size and perceived uniqueness on adoption intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 88(C).
    8. Petr Parshakov & Iuliia Naidenova & Sofia Paklina & Nikita Matkin & Cornel Nesseler, 2025. "Users Favor LLM-Generated Content -- Until They Know It's AI," Papers 2503.16458, arXiv.org.
    9. Kumar, Aman & Shankar, Amit & Hollebeek, Linda D. & Behl, Abhishek & Lim, Weng Marc, 2025. "Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption," Journal of Business Research, Elsevier, vol. 189(C).
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    11. Cao, Zhongpeng & Zhao, Liben & Su, Tong, 2026. "Does it matter who owns the AI device? Impact of device ownership on customer dissatisfaction in AI service failure," Journal of Retailing and Consumer Services, Elsevier, vol. 90(C).

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