AI Conversational Systems: Evolution, Architecture, and Future Directions
Year: 2026
Type: article
Abstract: Artificial intelligence (AI) has kind of emerged as a revolutionary paradigm, and it is influencing a lot of different industries, like healthcare education finance, and industrial automation. Chatbot systems, among its many applications, sort of act as an important interface that enables natural human–machine interaction, which sounds simple but is actually quite complex. This work provides a thorough theoretical analysis that ties together core AI concepts to more advanced chatbot systems. It looks at how AI progresses from symbolic systems toward data-driven models, then it extends the discussion into conversational agents that are powered by Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL). Along the way, the study discusses computational mechanisms application domains research challenges and also some newer trends, with a special focus on multilingual and low-resource conversational systems. The work kind of ends by outlining future directions for AI-powered chatbot systems, aiming for intelligence, ethical behavior, and context-awareness, even though people sometimes forget the last part.
Authors: Bonde, Seema S., Rane, Pallavi N.
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7219134837