This paper presents a comprehensive survey of the evolution and deployment of LLM-based AI chatbots across various sectors. It begins by summarizing the development of foundational chatbots, followed by the evolution of large language models (LLMs), and then provides an overview of LLM-based chatbots currently in use and those in the development phase. The paper explores the diverse applications of AI chatbots across industries, discusses open challenges related to data usage and knowledge generation, and outlines future directions for improving their efficiency and reliability. The survey highlights the transformative impact of LLMs on chatbot technology, enabling more sophisticated interactions and applications in education, research, healthcare, and other domains. It also addresses key challenges such as knowledge recency, hallucination, ethical considerations, and data privacy. The paper discusses the potential of LLM-based chatbots in various applications, including academic writing, data analysis, and medical consultations, while emphasizing the need for responsible usage and ethical guidelines. The survey concludes with a detailed overview of the current state of LLM-based chatbots, their capabilities, and future prospects.This paper presents a comprehensive survey of the evolution and deployment of LLM-based AI chatbots across various sectors. It begins by summarizing the development of foundational chatbots, followed by the evolution of large language models (LLMs), and then provides an overview of LLM-based chatbots currently in use and those in the development phase. The paper explores the diverse applications of AI chatbots across industries, discusses open challenges related to data usage and knowledge generation, and outlines future directions for improving their efficiency and reliability. The survey highlights the transformative impact of LLMs on chatbot technology, enabling more sophisticated interactions and applications in education, research, healthcare, and other domains. It also addresses key challenges such as knowledge recency, hallucination, ethical considerations, and data privacy. The paper discusses the potential of LLM-based chatbots in various applications, including academic writing, data analysis, and medical consultations, while emphasizing the need for responsible usage and ethical guidelines. The survey concludes with a detailed overview of the current state of LLM-based chatbots, their capabilities, and future prospects.