receiving, at a chatbot switching system with a processor, a first set of data in real-time, wherein the first set of data is associated with a plurality of users, wherein the first set of data comprising user behavioral information, past engagements with conversational agents and user profile information;

collecting, at the chatbot switching system with the processor, a second set of data in real-time, wherein the second set of data is associated with the one or more intelligent conversational agents, wherein the second set of data comprising a trust score associated with each of the one or more intelligent conversational agents, confidence level of the one or more intelligent conversational agents, past performance of the one or more intelligent conversational agents, and performance of each of the one or more intelligent conversational agents in a virtual environment;

fetching, at the chatbot switching system with the processor, one or more queries from the plurality of users for a mega bot, wherein the one or more queries are associated to a scope of field, wherein each of the one or more queries has a plurality of aspects, wherein the plurality of aspects comprising context, linguistic style, sentence construction, and lexical ambiguity;

analyzing, at the chatbot switching system with the processor, the first set of data, the second set of data and the one or more queries using one or more machine learning algorithms, wherein the analysis is performed based on training of a machine learning model, wherein the analysis is performed for enabling selection of a suitable intelligent conversational agent from the one or more intelligent conversational agents, wherein the analysis is performed in real time;

selecting, at the chatbot switching system with the processor, the suitable intelligent conversational agent from the one or more intelligent conversational agents having the trust score above a threshold level according to the plurality of aspects of each of the one or more queries, wherein the selection is based on the plurality of factors and the analysis of the first set of data, the second set of data and the one or more queries, wherein the mega bot selects the suitable intelligent conversational agent from the one or more intelligent conversational agents, wherein the threshold level is defined by an enterprise, wherein the plurality of factors comprising identification of the plurality of aspects, confidence level of the one or more intelligent conversational agents, past performance of the one or more intelligent conversational agents, behavior identification of the plurality of users, automated testing performance of the one or more intelligent conversational agents, performance of each of the one or more intelligent conversational agents in the virtual environment, cost of engagement with the one or more intelligent conversational agents and a feedback from the plurality of users;

creating, at the chatbot switching system with the processor, responses for the one or more queries using the suitable intelligent conversational agent from the one or more intelligent conversational agents;

creating a secondary response for the one or more queries in a virtual environment with a privacy rule limitation, wherein the privacy rule limitation corresponds to sharing the one or more queries with the one or more intelligent conversational agents not sharing the first set of data with the one or more intelligent conversational agents;

analyzing, at the chatbot switching system with the processor, the second response of the one or more intelligent conversational agents and improving the trust score of the one or more intelligent conversational agents based on the analysis of the second response; and

switching, at the chatbot switching system with the processor, between the one or more intelligent conversational agents in the mega bot interacting with the plurality of users based on the plurality of aspects of corresponding query of the one or more queries and the plurality of factors.