Conversational AI refers to the technology that enables computers or machines to engage in natural, human-like conversations with users. It combines various fields such as natural language processing (NLP), natural language understanding (NLU), machine learning, generative AI (GAI) and artificial intelligence (AI) to understand and respond to human input in a conversational manner.

Conversational AI systems are designed to understand and interpret human language, both written and spoken, and generate appropriate responses. They aim to mimic human conversation by providing contextually relevant and meaningful interactions. These systems can be found in a wide range of applications, including virtual assistants, chatbots, voice assistants, customer service platforms, and more.

To achieve conversational capabilities, AI models like GPT-4o are trained on large amounts of text data to learn the patterns, context, and semantics of human language. They can then generate coherent and contextually appropriate responses based on the input they receive. Conversational AI systems can also employ techniques like sentiment analysis, intent recognition, and entity extraction to better understand user queries and provide accurate responses.

Overall, conversational AI technology has rapidly evolved in recent years, and its applications continue to grow. It aims to enhance user experiences, improve customer service, and enable more efficient interactions between humans and machines in various domains. It seems to be most widely used in call center automation and web customer service automation.

Examples of Conversational AI platforms commercially available include the following from Gartner

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