Reconceptualizing Service Quality in Generative AI–Enabled Banking: Evidence from India

Abstract

The fast uptake of generative artificial intelligence (GenAI) in banking services has altered the way customers interact with the company and casts doubt on the suitability of traditional models of service quality that had been created to operate in a human-mediated context. This paper reframes service quality as a connection to generative AI-based banking by the investigation of whether the traditional SERVQUAL dimensions are enough to describe customer assessments in intelligent financial ecosystems. The research suggests a newer framework that includes TrustQuality, InteractionQuality, Tangibles, Satisfaction, and BehaviouralIntention, based on the assumption that customers are increasingly evaluating the banking services based on integrated perceptions of trust, responsiveness, personalization and intelligent interaction. The quantitative research design was used and 205 AI-enabled banking service users were surveyed in India as primary data. In order to investigate the suggested correlations and demonstrate the improved framework's explanatory capacity, we used partial least squares structural equation modeling (PLS-SEM). According to the findings, however Tangibles do not significantly affect customer happiness, InteractionQuality and TrustQuality do. Customer satisfaction was shown to be a strong predictor of behavioural intention, which explains why AI-enabled banking services were intended to be used and recommended by consumers. The model shows that it can predict a significant amount of variance of Satisfaction and BehaviouralIntention through 77.6 and 78.8 respectively. This research serves as a contribution to the field of service quality theory, where the authors have shown that customer assessments of generative AI-founded banking are becoming gradually manifested in multidimensional perceptions of trust and interaction, and not as the splintered traditional service dimensions. The results present an updated service quality architecture of intelligent banking settings and also present viable recommendations to financial firms seeking to undergo AI-driven service transformation.