Conversational agents, which understand, respond to, and learn from each interaction using Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Multi Dialog Management, and Machine Learning (ML), have become more common in recent years. Conversational agents, also called chatbots, are used to have real-time conversations with individuals. As a result, conversational agents are now being used in various sectors, including education, healthcare, marketing, customer assistance, and entertainment. Conversational agents, frequently used as chatbots and virtual or AI helpers, show how computational linguistics is used in everyday life. It can be challenging to pinpoint the variables that affect the use of conversational agents for business acceleration and defend their utility to enhance export companies. This paper summarises the evolution of conversational agents from a straightforward model to a sophisticated, intelligent system and how they are applied in various practical contexts. This study contributes to the literature on information systems by contrasting the different conversational agent types based on the export business acceleration interface. This paper also identifies the challenges conversational applications experience today and recommends further research.