The search for AI value: The role of complexity in human-AI engagement in the financial industry

Abstract

The banking industry is infusing AI systems into service encounters while dissolving some traditional services. This study aims to empirically test an exploratory framework to identify how human-AI interactions differ when engaged in basic or advanced virtual agent usage contexts. A conceptual framework was developed to examine consumer perceptions of basic and advanced virtual agent usage intentions. Five independent variables of trust in AI, perceived security in AI, perceived AI expertise, comfort in using AI technologies, and need for social presence were explored. Data was collected from 322 respondents and analyzed using multivariate regression. The findings suggest that consumers do not perceive service encounters with virtual agents from a “one size fits all” approach. Consumers perceive different value-in-use perceptions based on the complexity of the usage contexts. Our results suggest that success in advanced virtual agent encounters may require social presence for robust human-AI interaction. Additionally, this study extends the digital servitization and service robot acceptance model (sRAM) literature by evaluating consumer value-in-use perceptions with empirical evidence.