In developing countries such as India, mobile health applications are changing the healthcare landscape. Through the use of artificial intelligence (AI), these applications deliver personalized healthcare services, enhance healthcare accessibility, facilitate early diagnosis, and support remote monitoring. The market of mobile health apps is growing in India, and there is cutthroat competition among developers to improve AI features with significant investment. To stay competitive, mobile health service providers and mobile health app developers must understand how users perceive these AI features and their impact on overall satisfaction and health outcomes. This study employed expectation-confirmation theory (ECT) to understand how AI features influence the satisfaction of users through expectation confirmation and perceived performance. The literature review covers ECT, ECT and information systems, AI features in mobile health apps leading to a research model that explains relationships between AI features, expectation confirmation, perceived performance, and user satisfaction. Hypotheses based on ECT suggest that exceeding or meeting user expectations enhances user satisfaction, leading to sustained app usage and positive word of mouth. The proposed research model provides a framework for future studies. Researchers can validate the proposed research model using conclusive research and help developers refine mobile health apps to better meet user needs and maintain high user retention rates in a competitive market like India.