Smart tech, happy customers: The AI impact on satisfaction

Omar, Siti Sarah and Teoh, Wendy Ming Yen and Azman, Naqibah and Yeo, Zi Xwan and Abdullah, Intan Nur Sakinah and Mochamad Nasir, Nur Nisa (2025) Smart tech, happy customers: The AI impact on satisfaction. paperASIA, 41 (5b). pp. 39-47. ISSN 0218-4540

Text 0270309102025827492285.pdf Available under License Creative Commons Attribution Non-commercial. Download (801kB)

Abstract

In customer service, artificial intelligence (AI) has emerged as a disruptive force that is transforming how companies interact with customers and address their needs. This study aims to explore how AI-driven solutions such as chatbots, engine-based recommendations, and sentiment analysis affect customer satisfaction levels. Quantitative method, including a questionnaire, was utilized in this study. The questionnaire was divided into three sections: Section A (demographics), Section B (organization and customer agility, customer experience, and customer relationship quality), and Section C (customer satisfaction). Primary data was collected from a sample of 128 respondents, all of whom are students at Universiti Tun Hussein Onn Malaysia (UTHM). To analyze the data, SPSS 29 was employed. The findings indicate a positive and significant relationship between organizational and customer agility, customer experience, and the quality of customer relationships on customer satisfaction in AI. Although the study achieved important insights, it also acknowledges limitations such as time constraints and a relatively small sample size. This investigation contributes to a deeper understanding of the key drivers of customer satisfaction, highlighting how AI supports agility, relationship quality, and experience enhancement.

Item Type:	Article
Uncontrolled Keywords:	Organization and customer agility, Customer experience, Customer relationship quality, Customer satisfaction
Divisions:	Institute of Technology Management And Entrepreneurship
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	18 May 2026 02:01
Last Modified:	18 May 2026 02:01
URI:	http://eprints.utem.edu.my/id/eprint/29908
Statistic Details:	View Download Statistic

Actions (login required)

View Item