Examining the impacts of artificial intelligence characteristics on user resistance to financial robo-advisors
Jung-Chieh Lee, Siqi Jiang, Yuyin Tang
Abstract
Purpose Currently, artificial intelligence (AI) is being utilized to improve and strengthen the function of financial technology (fintech), especially for AI-enabled financial robo-advisors in consumer markets. Nevertheless, how AI characteristics affect users’ resistance to the use of AI advisors remains unclear. To address this gap, this paper employs innovation resistance theory (IRT) to propose a research model to further explore the effects of intelligence and anthropomorphism (AI characteristics) on users’ resistance to robo-advisors via functional (usage, value and risk barriers) and psychological (traditional and image barriers) barriers. Design/methodology/approach A total of 482 AI-enabled financial robo-advisor users were used as a sample to examine the model. Partial least squares (PLS) was utilized to perform the data analysis. Findings The results indicate that the intelligence of AI-enabled robo-advisors reduces resistance, whereas the anthropomorphism of AI-enabled robo-advisors increases resistance. In addition, intelligence significantly reduces usage, value, tradition and image barriers, which in turn decreases users’ resistance to AI-based robo-advisors. Interestingly, anthropomorphism significantly increases usage and value barriers, which ultimately leads to increased resistance to AI-based robo-advisors. Originality/value This study provides a theoretical contribution to the literature by examining how intelligence and anthropomorphism affect users’ functional and psychological barriers in the context of AI-based robo-advisor resistance. The findings of this study are important for financial institutions seeking to use AI to reduce users’ resistance to robo-advisors and increase financial inclusion.