When do you trust AI? The effect of number presentation detail on consumer trust and acceptance of AI recommendations
Abstract
When do consumers trust artificial intelligence (AI)? With the rapid adoption of AI technology in the field of marketing, it is crucial to understand how consumer adoption of the information generated by AI can be improved. This study explores a novel relationship between number presentation details associated with AI and consumers' behavioral and evaluative responses toward AI. We theorized that consumer trust would mediate the preciseness effect on consumer judgment and evaluation of the information provided by AI. The results of five studies demonstrated that the use of a precise (vs. imprecise) information format leads to higher evaluations and behavioral intentions. We also show mediational evidence indicating that the effect of number preciseness is mediated by consumer trust (Studies 2, 4, and 5). We further show that the preciseness effect is moderated by the accuracy of AI‐generated information (Study 3) and the objective product quality of the recommended products (Study 4). This study provides theoretical implications to the AI acceptance literature, the information processing literature, the consumer trust literature, and the decision‐making literature. Moreover, this study makes practical implications for marketers of AI businesses including those who strategically use AI‐generated information.
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Trust functioned as a significant mediator through which expertise was related to reliance, enabling or inhibiting adjustments based on AI advice.
“Our findings suggest trust functioned as a significant mediator through which expertise was related to reliance, enabling or inhibiting adjustments based on AI advice and confirming previous research (Kim et al., 2021;Schemmer et al., 2022).”
From Investigating appropriate reliance on AI-Based decision support systems: the role of expertise, trust, and self-confidence (2025) · cites this paper as Kim et al., 2021
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References 88 · Cited by 353
- Authors
- Kim, J., Giroux, M., & Lee, J. C.
- Affiliations
- Auckland University of Technology (NZ)
- Dongguk University (KR)
- Corresponding author
- Lee, Jacob C.
- Venue
- Psychology & Marketing
- Publisher
- Wiley
- Published
- 2021-05-08
- Volume
- 38
- Issue
- 7
- Pages
- 1140-1155
- ISSN
- 0742-6046 (ISSN-L)
- 1520-6793
- OpenAlex
- W3163498617
- Cited by
- 353
- References
- 88
- Citations by year
- 2026: 116 · 2025: 116 · 2024: 63 · 2023: 33 · 2022: 21 · 2021: 4
- FWCI
- 10.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychology and Marketing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Keywords
- artificial intelligence, consumer trust, AI-generated recommendations, AI acceptance, consumer evaluation, behavioral intention, AI accuracy, product quality, purchase decision, information processing
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