A randomized controlled trial will evaluate whether a conversational AI chatbot can improve quality of life in 480 adults with atrial fibrillation over three months. The CHAT-AF-S intervention aims to enhance patient self-management through human-like digital conversations, measuring outcomes using the Atrial Fibrillation Effect on Quality-of-life (AFEQT) scale. This represents a significant shift toward AI-powered patient support in cardiovascular care. Atrial fibrillation affects millions globally, causing reduced quality of life and increased stroke risk. Traditional self-management education often lacks engagement and accessibility. Conversational AI could provide 24/7 personalized support, potentially filling gaps in clinical care between appointments. The technology's ability to simulate natural dialogue may improve patient adherence to medication and lifestyle modifications compared to static educational materials. However, this study protocol describes future research rather than completed findings. The effectiveness of AI chatbots in chronic disease management remains largely unproven, with questions about patient acceptance, clinical integration, and long-term engagement. As this is a preprint protocol awaiting peer review, the actual trial results and their interpretation may differ from the proposed methodology once the study concludes.