Impact of Artificial Intelligence (AI) on Service Quality and Customer Experience in the Banking Sector: An Empirical Study of National Capital Region (NCR), India

Authors

  • Ritu Talwar NDIM, New Delhi, India.
  • Savita P. Vaidya Mangalvedhekar Institute of Management, Maharashtra, India.

DOI:

https://doi.org/10.70917/ijcisim-2026-3685

Keywords:

Artificial Intelligence, Digital Banking, Customer Experience, Service Quality

Abstract

The Indian banking industry has undergone a remarkable transformation over the last decade, driven by rapid technological advancements and the increasing integration of Artificial Intelligence (AI). AI-powered banking solutions such as intelligent chatbots, predictive analytics, biometric authentication, fraud detection systems, robotic process automation, and personalized financial advisory services have significantly improved operational efficiency while enhancing customer satisfaction. The National Capital Region (NCR), comprising Delhi, Gurugram, Noida, Ghaziabad, and Faridabad, represents one of India's most digitally advanced banking ecosystems, making it an ideal setting to examine the influence of AI on banking services.The present study investigates the impact of Artificial Intelligence on service quality and customer experience among public and private sector banks operating in NCR. The research adopts a quantitative research design using structured questionnaires administered to 500 banking customers across NCR. Statistical tools including descriptive statistics, reliability analysis, correlation, regression analysis, and hypothesis testing are proposed to evaluate the relationship between AI adoption and customer satisfaction.

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Published

2026-07-24

How to Cite

Ritu Talwar, & Savita P. Vaidya. (2026). Impact of Artificial Intelligence (AI) on Service Quality and Customer Experience in the Banking Sector: An Empirical Study of National Capital Region (NCR), India. International Journal of Computer Information Systems and Industrial Management Applications, 18(10s), 304–311. https://doi.org/10.70917/ijcisim-2026-3685

Issue

Section

Original Articles