Three stages were taken to find and evaluate pertinent publications for this systematic literature re: Figure 2. Database used for the search Figure 4. Different types of chatbot and its application The framework establishes a standard for using AI in social media customer su pport initiatives. It suggests that to improve client interactions on the internet, computerized but sympathetic exchanges may become more prevalent(Xu et al., 2017). It is a flexible answer for interpersonal req range of industries because of its efficacy and versatility. The long-term impacts of an uirements across a hropomorphism in chatbot encounters might be investigated in more detail. Investigating how chatbot design might improve buyer happiness and connection to emotions(Araujo, 2018). Additional studies migh erating effects of particular organizational characteristics on the association between examine the mod- the use of chatbots and their results. Research might look at the advantages of chatbots for work vs non-work for workers as well as other business consequences that emerge from using them in companies(Wang et al., 2022). Intent Recognition: The chatbot chooses the right answer by identifying the user’s intent based o1 the input it has received. Using machine learning models to classify user input and determine the user’: intended goal is known as intent recognition. Response Generation: The chatbot uses established templates or language generation models to construct a response after determining the user’s intent and retrieving the required data. The user is then informed of this response.
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