Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 2785–2791
Article DOI: 10.30574/wjaets.2025.15.2.0834
Received on 15 April 2025; revised on 27 May 2025; accepted on 29 May 2025
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.
Natural Language Processing; Machine Learning; Hybrid Human-Ai Models; Omnichannel Integration; Personalization Mechanisms
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Rajkumar Gopalakrishnan. Conversational AI in customer service: Transforming user interactions with NLP and Machine learning. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 2785–2791. Article DOI: https://doi.org/10.30574/wjaets.2025.15.2.0834.