Restoring Service Quality and Trust in AI Enabled Bank Customer Service: A Case Study of Digital Transformation Misalignment

Abstract

This paper examines how the implementation of artificial intelligence (AI) in bank customer service contributed to declining service quality and customer trust despite achieving operational cost savings. The case involves a large bank that reduced labor costs by 19% after deploying AI enabled customer service, yet experienced a 300% increase in customer complaints and a 9% loss of customers. The purpose of this paper is to evaluate the organizational causes of the failed digital transformation and recommend evidence-based strategies for improving service quality and restoring customer trust. A narrative literature review was conducted using research on AI in service operations, service quality, trust in automation, digital transformation, service recovery, and organizational change. The analysis found that the bank overrelied on automation, failed to align AI capabilities with customer needs, and lacked sufficient governance and human escalation processes. The paper applies the Balanced Scorecard, Kotter's Eight Step Process, and Saldanha's Digital Transformation Discipline to interpret the case and develop recommendations. The findings suggest that AI creates greater value when it supports rather than replaces human employees and when organizations balance efficiency with customer experience, governance, and trust. This paper contributes practical recommendations for leaders seeking to implement AI responsibly while improving long term organizational performance and customer relationships.

KEYWORDS: Artificial Intelligence, Customer Service, Digital Transformation, Service Quality, Trust