Support for Businesses’ Use of Artificial Intelligence: Dynamics of Trust, Distrust, and Perceived Benefits

Lisa Tam, Soojin Kim and Yi Gong
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Lisa Tam: School of Advertising, Marketing and Public Relations, Queensland Technology of Technology, Australia
Soojin Kim: School of the Arts and Media, University of New South Wales, Australia
Yi Gong: School of Advertising, Marketing and Public Relations, Queensland Technology of Technology, Australia

Media and Communication, 2025, vol. 13

Abstract: Current research on AI has extensively examined drivers that predict individuals’ attitudes and behavioral intentions toward AI use. Despite this, there is limited research that explores factors that influence consumers’ acceptance of AI integration into businesses. As more businesses have integrated AI systems into different aspects of their operations, consumers have experienced increasing interactions with AI systems adopted by businesses. Thus, it is critical to understand not only whether individuals trust and accept the use of AI in their everyday lives, but also whether they trust and accept the use of AI by businesses they interact with. As such, this study tests a theoretical framework developed on the basis of current research on AI and technology acceptance. This study used a survey dataset collected from a nationally representative sample of 420 Australian consumers in 2024. The findings revealed that the interplay between faith in general technology, trust and distrust in businesses' AI use, and perceived AI benefits shaped attitudes and behavioral intentions toward businesses using AI. These dynamics also contributed to the approval of businesses’ use of AI. The findings offer theoretical and practical insights on how to manage these dynamics to foster positive attitudes and behavioral intentions toward businesses that use AI.

Keywords: artificial intelligence; consumers; distrust; faith in technology; perceived benefits; trust (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v13:y:2025:a:9534

DOI: 10.17645/mac.9534

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