From Artificial Intelligence to Customer Advocacy: Evidence from the Banking Industry

Abstract

Research Originality: This study contributes to the literature by integrating technological, relational, and behavioral perspectives and mechanisms to explain how AI-enabled banking services may translate into customer advocacy through Brand Trust, Customer Engagement, and Customer Satisfaction. Research Objectives: This study examines the direct and indirect effects of Artificial Intelligence on Brand Trust, Customer Engagement, Customer Satisfaction, and positive word-of-mouth (PWOM), with particular attention to the mediating roles of these customer relationship constructs. Research Method: We surveyed 484 Indonesian banking customers using AI-enabled services and analyzed the data through Partial Least Squares Structural Equation Modeling (PLS-SEM).   Empirical Results:  The findings indicate that AI capability positively influences Brand Trust, Customer Engagement, and PWOM, with Brand Trust emerging as the most prominent mechanism associated with customer advocacy. Customer Engagement also positively influences Customer Satisfaction; however, Customer Satisfaction does not significantly influence PWOM. Implications:  The findings suggest that successful AI implementation in banking should extend beyond technological performance to encompass relationship building. Strengthening Brand Trust should therefore be a strategic priority, as trust appears to provide a stronger foundation for customer advocacy than Customer Satisfaction alone. JEL Classification: G21, G41, M15, O33