Nowadays, road accidents have become a serious concern for road fatalities, product damage, injuries, and many other losses. When an accident takes place, we immediately need to find out the root causes and the respective preventive measures to avoid the recurrence of such types of incidents. Various workflow strategies are used during the process of root-cause-analysis, but in this paper, we have implemented a “why-why analysis”-based method by designing a conversational artificial intelligence (AI) named root cause failure analysis (RCFA). The design of the chatbot uses a rule-based framework, where the user needs to answer some questions, and based on the user’s responses, the chatbot will provide the root causes along with the respective preventive measures to avoid recurrences. In our paper, we have used a cloud-based platform named Botpress as this is much more suitable for designing a rule-based chatbot. The proposed RCFA chatbot has achieved containment rate of 81.48%, which is 3.93% improvement over an existing AI-based chatbot with a containment rate of 78.40%.