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Chatbots vs Conversational AI: The Difference Explained

Asking the difference between a chatbot and conversational AI is like asking the difference between cherry pie and cooking. Even though these terms are related, they’re not synonymous. A chatbot is a tool that emulates human-like conversations with users, while conversational AI is the technology that makes the creation of sophisticated AI-powered chatbots possible. That constitutes all the difference, and we could finish here. But we won’t because otherwise you won’t learn the fine details and we won’t be able to rank such a short article on Google. So let’s help each other, shall we? In the following paragraphs, we will discuss the “chatbot vs conversational AI” question and elaborate on the difference between the two terms. You will: Learn what a chatbot and conversational artificial intelligence are; See some examples of chatbots and conversational AI implementations; Discover how chatbots and conversational AI systems differ. Without further ado, let’s get started! What is a chatbot? A chatbot is a software application that emulates human-like conversations with users. Chatbot solutions help elevate customer experience while decreasing customer service costs. No wonder the chatbot market is forecast to reach around $1.25 billion in 2025. Such applications reply instantly, can work 24/7, and sometimes replace customer support teams altogether—that’s why businesses eagerly invest in chatbot development. It’s important to know that there are two types of chatbots: Rule-based chatbots (also known as script-based chatbots or basic chatbots). These applications communicate through pre-programmed rules: if a user says “X”, reply with “Y”. Basic chatbots don’t understand human language and can’t learn from conversations. Consequently, they are unable to reply to new questions and get confused when the user phrases their question in an unusual way. Looking on the bright side, rule-based chatbots are relatively cheap to develop and maintain. AI-powered chatbots. AI-powered chatbots use artificial intelligence, machine learning, and natural language processing to understand the intent behind user queries and provide more human-like responses. They can understand human language (as far as technology does this) and learn from conversations. Unlike basic solutions, AI-driven conversational bots can respond to any question, regardless of how it is phrased. They take customer experience to a whole new level and can serve as a substitute for human customer support teams. However, such solutions are expensive to develop and maintain. When talking about conversational AI technology, people usually refer to AI chatbots. What is conversational AI? Conversational AI is the technology that allows the creation of AI-powered chatbots. With the help of speech recognition and machine learning, conversational AI chatbot understands what people are saying, the conversion context, and the user intent behind queries. Unlike traditional chatbots, AI solutions can support multiple communication channels, including voice and video. According to a report by MIT Technology Review, over 90% of businesses see significant improvements in complaint resolution, call processing, and customer and employee satisfaction with conversational AI chatbots. The main difference between conversational AI solutions and chatbots is that the former is a technology while the latter is a software product. Of course, conversational AI is implemented not only in chatbots but also in: Voice assistants. Voice assistants are software programs that perform certain tasks based on voice commands. They use voice recognition, voice synthesis, and language processing algorithms to understand the command and provide the necessary outputs. Siri is one of the most popular examples of voice assistants. Virtual assistants (virtual agents). Virtual assistants are AI-based context-aware programs that help users perform specific tasks. They're powered by NLP and natural language understanding (NLU) models, which allows them to provide more personalized, accurate, and engaging outputs.