ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI in Finance
Volume 8 - 2025 | doi: 10.3389/frai.2025.1623534
Artificial Intelligence Attitudes and Resistance to Use Robo-Advisors: Exploring Investor Reluctance toward Cognitive Financial Systems
Provisionally accepted
- 1Chitkara Business School, Chitkara University, Punjab, India
- 2CBS International Business School, CBS University of Applied Sciences, Mainz, Germany
- 3Christ university, Delhi, India
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The study investigates resistance towards Financial Robo-Advisors (FRAs) among retail investors in India, grounded in innovation resistance theory. The study examines the impact of functional barriers and psychological barriers on resistance to FRAs, while considering user's attitudes towards Artificial Intelligence (AI) as a moderator. It further evaluate the influence of such resistance on users' intentions to use and recommend FRAs. Utilizing purposive sampling data was collected from 409 investors and further analyzed using structural equation modelling. The findings revealed that all barriers under study, expect value barrier, substantially derive resistance towards robo-advisors, with inertia being the strongest determinant. Further, this resistance impedes both the intention to use FRAs and to recommend them. Moderation analysis results finds that users' attitude towards AI significantly weakens the influence of inertia, overconfidence bias and data privacy risk on resistance, with no such impact on other relationships. Overall, the study enriches IRT in Fintech context and provides theoretical and practical insights to enhance FRAs adoption in emerging markets.
Keywords: Attitude towards AI, Robo-Advisors, artificial intelligence, Resistance, FRA, Cognitive Financial Systems
Received: 03 Jun 2025; Accepted: 19 Aug 2025.
Copyright: © 2025 Verma, Schulze, Goswami and Upreti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Balraj Verma, Chitkara Business School, Chitkara University, Punjab, India
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