• Arun Raju Chinna Raju

The study focuses on the integration of AI and NLP in the automation of customer service, and their evolution from theory to actual implementations. Building on core principles of AI, such as the Turing Test, as well as customer service frameworks like SERVQUAL and the Kano Model, the research creates a holistic theoretical grounding. The study delves into fundamental areas of NLP (such as syntactic, semantic, and pragmatic analysis) as well as advanced AI architectures ranging from traditional machine learning to cutting-edge transformer models like BERT and GPT, demonstrating their role in improving customer experiences. It researches implementation frameworks such as RASA, Dialog flow, and Microsoft's Bot Framework, focusing on scalability as well as customization. Effectively resisting trust and fairness in any AI systems, ethical feasibility like as privacy protection, mitigation of bias and transparency in preventing AI systems are thoroughly scrutinized. Both types of performance metrics – technical (like BLEU and ROUGE scores) and customer-oriented processes (like NPS and CSAT) are combined for a complete view of the efficiency of the system. Emerging trends such as multimodal AI, emotional computing, federated learning and quantum NLP reflecting innovations that improve user interaction and obtain sensitivity to privacy. With the research, practitioners and researchers will be able to advance the application of AI-powered solutions in customer-facing services while promoting trustworthiness in human-AI delegation of customer service tasks.

Artificial Intelligence, Natural Language Processing, Customer Service Automation, Machine Learning, Deep Learning, Sentiment Analysis, Chatbots, Ethics in AI, Performance Metrics, Human-AI Collaboration, Multimodal AI, Emotional Computing, Federated Learning, Quantum NLP, Service Quality, Privacy Protection, Bias Mitigation, System Transparency.

"ADVANCING AI-DRIVEN CUSTOMER SERVICE WITH NLP: A NOVEL BERT-BASED MODEL FOR AUTOMATED RESPONSES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 1, page no.h89-h123, January-2025, Available :http://www.jetir.org/papers/JETIR2501712.pdf

"ADVANCING AI-DRIVEN CUSTOMER SERVICE WITH NLP: A NOVEL BERT-BASED MODEL FOR AUTOMATED RESPONSES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 1, page no. pph89-h123, January-2025, Available at : http://www.jetir.org/papers/JETIR2501712.pdf