The Use of Artificial Intelligence Assistants in Consumer Purchase Decisions: The Mediating Role of Intention

Abstract

Purpose – This study aims to determine the direct effects of perceived benefit, trust, and risk factors on usage intention and purchase decisions within the context of AI-supported shopping processes. Furthermore, it investigates the mediating role of usage intention in the relationship between these independent variables and the purchase decision.
Design/methodology/approach – This quantitative research was conducted with 399 participants aged 18 and over who have generative AI applications installed on their smartphones and utilize these tools in their shopping experiences. Data were collected through convenience sampling. Descriptive statistics, correlation, and multiple regression analyses were employed for data analysis; additionally, the mediation effect was tested using the PROCESS Macro via the bootstrapping method (n=5000, with a 95% confidence interval).
Results – Analysis results indicate that perceived benefit and trust have a positive and significant effect on both usage intention and purchase decisions. Usage intention was identified as the strongest predictor of purchase decisions (β= .463). The direct effect of perceived risk on both usage intention and purchase decisions was found to be statistically insignificant. Moreover, it was determined that usage intention plays a partial mediating role in the effects of benefit, trust, and risk on purchase decisions.
Discussion – Although consumers harbor concerns regarding the privacy and security of their
personal data, they tend to disregard these concerns in favor of the conveniences offered by AI tools.
This suggests that as the perceived benefit of a product increases, the thresholds for tolerance
regarding its risks expand accordingly. This contradictory phenomenon, known in the literature as
the "privacy paradox," demonstrates that consumers tend to prioritize the benefits to be gained over
potential risks.