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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM54247
Volume:
9 |
11 |
Nov 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In today’s fast-moving world, businesses are always trying to find better ways to connect with their customers. It is not only about selling products or services anymore; how customers feel during their interaction with a company is very important. A good experience can make customers trust the business, return again, and even recommend it to others, while a bad experience can make them leave. To improve customer interactions and make services faster, many companies are now using AI-powered chatbots. These chatbots can answer questions instantly, give personalized responses, and handle many customers at the same time. For example, if a customer wants to check their order status or know how to return a product, a chatbot can provide quick answers without waiting in long queues. This saves time for customers and reduces the workload on human staff. Studies show that AI chatbots can lower customer service costs and improve response times, which benefits both customers and businesses. This research aims to evaluate the roles, effectiveness, and limitations of both chatbots and human agents in customer interaction. The study will compare their performance in terms of response time, accuracy, customer satisfaction, and empathy. It will also analyse how AI advancements such as Natural Language Processing (NLP) and Machine Learning (ML) are improving chatbot capabilities. The research further explores how human–AI collaboration can create an ideal balance between automation and personal connection. Data will be collected through surveys, to identify the best practices for integrating chatbots and human agents in modern organizations. Survey results (n=100) show chatbots score higher on speed and availability while human agents score higher on empathy and trust. The study recommends hybrid deployment with smooth escalation to improve overall satisfaction.
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Publication Date
11/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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