Artificial Intelligence (AI) has enabled the creation of intelligent systems capable of understanding and interacting with humans naturally. Among its many applications, the AI-based chatbot stands out as one of the most widely used and influential innovations. A chatbot is a conversational agent that uses Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL) to engage in human-like communication through text or speech. It can analyze queries, understand intent, and generate meaningful responses in real-time. This review paper provides a detailed study of AI chatbot development, architectures, methodologies, and use cases across domains such as education, healthcare, customer service, and e-commerce. It reviews more than 25 recent research papers (2020–2025) and integrates case studies of real-world systems like ChatGPT, IBM Watson, Google Bard, and Replika. The paper discusses the evolution of chatbots from early rule-based systems to transformer-based models, identifies current challenges such as context management, ethics, and scalability, and explores future trends in multimodal chatbots, emotion detection, and explainable AI.
Artificial Intelligence (AI), Chatbots, Natural Language Processing (NLP), Machine Learning (ML), Deep Learning, Conversational AI, Transformer Models, Generative AI.
IRE Journals:
Shweta Tarade, Tanvi Mokashie, Pranjali Yadav, Shreya Nikam, Prof. Prajwal pawar "AI-Based Chatbot Systems: Architectures, Applications, and Future Trends" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 785-797 https://doi.org/10.64388/IREV9I5-1711981
IEEE:
Shweta Tarade, Tanvi Mokashie, Pranjali Yadav, Shreya Nikam, Prof. Prajwal pawar
"AI-Based Chatbot Systems: Architectures, Applications, and Future Trends" Iconic Research And Engineering Journals, 9(5) https://doi.org/10.64388/IREV9I5-1711981