Artificial intelligence attitudes and resistance to use robo-advisors: exploring investor reluctance toward cognitive financial systems
subject: artificial intelligence; attitude toward AI; cognitive financial systems; FRA; resistance; robo-advisors
description: Introduction: 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 users attitudes towards Artificial Intelligence (AI) as a moderator. It further evaluate the influence of such resistance on users intentions to use and recommend FRAs. Methods: Utilizing purposive sampling data was collected from 409 investors and further analyzed using structural equation modelling. Results: 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. Discussion: Overall, the study enriches IRT in Fintech context and provides theoretical and practical insights to enhance FRAs adoption in emerging markets. Copyright 2025 Verma, Schulze, Goswami and Upreti.
creator: Verma, Balraj; Schulze, Mike; Goswami, Divya; Upreti, Kamal
source: Frontiers in Artificial Intelligence;Volume;8;Issue;;Article No.;1623534;
publisher: Frontiers Media SA
date: 01-01-2025
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 26248212;
format: online
language: English
type: Article
coverage: Verma B., Chitkara Business School, Chitkara University, Punjab, India; Schulze M., CBS International Business School, CBS University of Applied Sciences, Mainz, Germany; Goswami D., Chitkara Business School, Chitkara University, Punjab, India; Upreti K., Department of Computer Science, Christ University, Delhi, India