Gopalakrishnan, Rajkumar (2025) Conversational AI in customer service: Transforming user interactions with NLP and Machine learning. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2785-2791. ISSN 2582-8266
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Abstract
This article examines how conversational artificial intelligence (AI), powered by Natural Language Processing (NLP) and Machine Learning (ML), is transforming customer service operations across industries. It explores the technological foundations that enable machines to understand and respond to human language, including semantic analysis, intent recognition, and sentiment analysis capabilities. The discussion encompasses three architectural approaches—rule-based systems, AI-powered platforms, and hybrid human-AI models—highlighting their respective strengths and implementation contexts. Strategic considerations for effective deployment are addressed through an investigation of omnichannel integration and personalization mechanisms that enhance service delivery. The article presents empirical evidence demonstrating improvements in operational efficiency, scalability, and customer experience metrics following conversational AI implementation. By evaluating both technological capabilities and practical outcomes, this comprehensive overview provides insights into how organizations can leverage conversational AI to simultaneously improve service quality and operational performance.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.2.0834 |
Uncontrolled Keywords: | Natural Language Processing; Machine Learning; Hybrid Human-Ai Models; Omnichannel Integration; Personalization Mechanisms |
Depositing User: | Editor Engineering Section |
Date Deposited: | 16 Aug 2025 12:39 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4214 |