Adoption of AI-Powered Chatbots in Digital Financial Services: A Relational–Technological Model of Usage Intention

The recent expansion of conversational artificial intelligence has driven the integration of intelligent chatbots into various digital spaces, progressively transforming how people interact with technology-based services and platforms, particularly within digital financial services and FinTech ecosystems. Although much of the research on technology adoption continues to focus on functional variables associated with system utility and performance, understanding the role of relational dimensions in human–AI interaction remains limited. In this context, this study analyzes the relationships between relational experience, perceived technological quality, perceived usefulness, and behavioral intention to use chatbots, proposing a relational–technological model to understand the adoption of conversational systems in digital contexts. The research followed a quantitative approach with a predictive-explanatory cross-sectional design. The sample consisted of 398 users from Metropolitan Lima who had recently used AI-powered chatbots in digital financial services. Statistical analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that relational experience showed significant positive relationships with perceived technological quality, perceived usefulness, and behavioral intention to use AI-powered chatbots within the proposed structural model. Furthermore, perceived usefulness was found to partially mediate the relationship between relational experience and behavioral intention, although this indirect effect should be interpreted as complementary effect because of its modest magnitude. These findings suggest that the adoption of intelligent conversational systems is associated not only with the functional aspects of the system but also with users’ experiences when interacting with these technologies, highlighting the relevance of relational experience as a complementary dimension for understanding AI chatbot adoption in digital financial environments.

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Publication Details

Journal
Multimodal Technologies and Interaction
Published
2026-11-06
DOI
https://doi.org/10.3390/mti10110117
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Adoption of AI-Powered Chatbots in Digital Financial Services: A Relational–Technological Model of Usage Intention

Kerwin José Chávez Vera, Qorimayu Moisés Chávez Villanueva, Ariana Mercedes Zamora Nuñez
3 links
Multimodal Technologies and Interaction
AI in Service Interactions
article

Adoption of AI-Powered Chatbots in Digital Financial Services: A Relational–Technological Model of Usage Intention

Kerwin José Chávez Vera, Qorimayu Moisés Chávez Villanueva, Ariana Mercedes Zamora Nuñez
article en

Abstract

The recent expansion of conversational artificial intelligence has driven the integration of intelligent chatbots into various digital spaces, progressively transforming how people interact with technology-based services and platforms, particularly within digital financial services and FinTech ecosystems. Although much of the research on technology adoption continues to focus on functional variables associated with system utility and performance, understanding the role of relational dimensions in human–AI interaction remains limited. In this context, this study analyzes the relationships between relational experience, perceived technological quality, perceived usefulness, and behavioral intention to use chatbots, proposing a relational–technological model to understand the adoption of conversational systems in digital contexts. The research followed a quantitative approach with a predictive-explanatory cross-sectional design. The sample consisted of 398 users from Metropolitan Lima who had recently used AI-powered chatbots in digital financial services. Statistical analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that relational experience showed significant positive relationships with perceived technological quality, perceived usefulness, and behavioral intention to use AI-powered chatbots within the proposed structural model. Furthermore, perceived usefulness was found to partially mediate the relationship between relational experience and behavioral intention, although this indirect effect should be interpreted as complementary effect because of its modest magnitude. These findings suggest that the adoption of intelligent conversational systems is associated not only with the functional aspects of the system but also with users’ experiences when interacting with these technologies, highlighting the relevance of relational experience as a complementary dimension for understanding AI chatbot adoption in digital financial environments.

Multimodal Technologies and InteractionVol. 10(11)
Universidad San Ignacio de Loyola (PE)
Openalex Percentile: Top 12%
AI in Service Interactions
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