Abstract: A system and method for dynamically recommending set of potential courses of actions for a user within a search query are disclosed. The system receives search queries from a user and determines dialogue attributes and context variables based on these queries. It identifies query parameters and additional parameters, The system analyzes user preferences, and determines entities and variants based on the user's preferences and the conversation context. The system then determines the types of set of potential courses of actions to generate for the search queries. Further, the system retrieves set of potential courses of, associated applications, and integration parameters from databases based on the determined types. Using large language models (LLMs) in generative AI or conversation AI environments, the system generates responses and clickable elements corresponding to the search queries, incorporating the recommended set of potential courses of actions, applications, and deep integration parameters.