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Evaluating Consumer Trust in Artificial Intelligence-Based Customer Interaction Services: An Empirical Study of Consumers in Surat City

  • JOURNAL OF ADVANCE AND FUTURE RESEARCH
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Abstract

Artificial Intelligence (AI)-based customer support services have become increasingly important in modern business operations due to their ability to provide quick, efficient, and personalized customer interaction. Organizations across sectors such as e-commerce, banking, telecommunications, and healthcare are widely adopting AI-enabled systems including chat bots, virtual assistants, and automated response platforms to enhance customer experience and operational efficiency. However, consumer trust remains a critical factor influencing the acceptance and effectiveness of AI-based customer interaction services. The present study aims to evaluate consumer trust toward AI-based customer support services in Surat city and identify the major factors influencing consumer perception and satisfaction toward AI-enabled interactions. The study is based on descriptive and analytical research design using primary data collected from 102 respondents through a structured questionnaire. Convenience sampling technique was used for data collection. Statistical tools such as percentage analysis mean and standard deviation, correlation analysis, Likert scale analysis, and Chi-Square test were applied for data interpretation. The findings of the study indicate that consumers generally have moderate to high trust toward AI-based customer support services. Quick response, reliability, accuracy, and consumer satisfaction were identified as significant factors positively influencing consumer trust. However, concerns regarding privacy, security, and lack of human empathy continue to affect consumer confidence toward AI-enabled systems. The study concludes that businesses must focus on improving transparency, service reliability, and data security to strengthen consumer trust and enhance the effectiveness of AI-based customer support services.

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DOI
10.56975/jaafr.v4i5.509469
OpenAlex
W7160609808
Document type
article
Language
EN
Source
JOURNAL OF ADVANCE AND FUTURE RESEARCH
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