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Balancing Cost Efficiency and Customer Loyalty: Redesigning AI-Enabled Customer Service in a Large Bank

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  • Wellesley R. Rogers

    (Marymount University, USA)

Abstract

The rapid adoption of artificial intelligence (AI) in banking has created a tension between cost efficiency and the trust-based relationships that underpin customer loyalty. This paper analyzes a large bank’s AI-enabled customer service transformation, during which a 19% reduction in personnel costs coincided with a 300% increase in customer complaints and a 9% customer loss. Drawing on research on AI service quality, trust, and reputational capital, chatbots in financial services, digital transformation strategy, and change management, the study diagnoses the bank’s core failure as the use of AI as a cost-focused gatekeeper rather than a human-aligned service capability. Using the Integrated Methodological Framework for Digital Transformation Strategy (IMFDS) and the ADKAR change management model, the paper links technical design choices and leadership decisions to darkside outcomes such as technological debt, perceived powerlessness, and erosion of trust. The analysis concludes with an evidence-based redesign of the bank’s service model, including a hybrid human–AI architecture, sentiment-driven escalation, AI quality assurance governance, and explainable AI (XAI) to restore transparency and accountability. These recommendations offer a practical roadmap for financial institutions seeking to balance automation with sustainable customer relationships in AIenabled service environments.

Suggested Citation

  • Wellesley R. Rogers, 2026. "Balancing Cost Efficiency and Customer Loyalty: Redesigning AI-Enabled Customer Service in a Large Bank," RAIS Conference Proceedings 2022-2025 0630, Research Association for Interdisciplinary Studies.
    • Handle: RePEc:smo:raiswp:0630
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