AI vs. Humans in U.S. Retail Banking: A Pilot Study on Customer Satisfaction and Service Excellence
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose. This pilot study aims to explore the perceived effectiveness of artificial intelligence (AI) and human interaction models within a university-affiliated sample, focusing on U.S. retail banking customer satisfaction and service excellence. Design / Method / Approach. The pilot study involved 50 participants from a university community—U.S. retail banking customers affiliated with Wright State University. A structured survey was conducted, and data were analyzed using descriptive statistics, predictive analytics, ANOVA, regression analysis, and t-tests to assess satisfaction levels, response times, and service preferences. Findings. Results indicate that human interaction consistently outperformed AI, with an average satisfaction score of 4.14 compared to 3.56 for AI (p<0.05). Male participants rated AI higher, whereas females preferred human interaction. Regression analysis revealed that AI satisfaction was primarily influenced by service consistency (p=0.035, R²=0.176), while human satisfaction was driven by personalized service (p=0.009, R²=0.220). These results suggest that empathy and personalization remain central to service excellence, while AI’s consistency can enhance operational efficiency. Theoretical Implications. The findings contribute to understanding the human–AI service trade-off by integrating behavioral and demographic dimensions into service design. Practical Implications. The study recommends enhancing the consistency of AI-driven systems and investing in employee training programs to strengthen empathy and personalization, which together foster loyalty and customer trust. Originality / Value. This work empirically substantiates the dual path toward technological efficiency and human-centric empathy, highlighting hybrid AI–human approaches as optimal for banking economics. Research Limitations / Future Research. Limited sample size and homogeneity restrict generalization; future research should employ larger, demographically diverse samples and longitudinal designs to explore mediating factors such as trust and cultural context. Article Type. Exploratory Research / Pilot Study.
DOI: 10.15421/cims.4.321
Author: Sifat Mahmud
Institution: Wright State University
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416719237