The advancement of technology in education has led to the development of interactive and personalized learning tools. This research focuses on creating mobile learning application with multimedia and AI support to improve student engagement, motivation, and academic performance in higher education. This research aims to answer the question: How effective is an AI-based mobile learning app with multimedia support in enhancing student interactivity, motivation, and performance in higher education? The research follows the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). Data was collected from expert validators (media and material experts) and student feedback. A quantitative descriptive analysis was done using Likert-scale instruments to measure user experience, interactivity, motivation, and learning outcomes. The application was tested on 38 students, and their feedback was used to assess its effectiveness. The results show that the AI-based mobile learning app significantly improved student interactivity, motivation, and academic performance. The post-test results showed an average score of 81.82%, indicating an improvement in learning outcomes. Students expressed high satisfaction with the app’s interactivity, multimedia content, and personalized learning paths. The AI-driven real-time feedback contributed to a more engaging learning experience. In conclusion, the AI-based mobile learning app with multimedia support effectively enhances student engagement, motivation, and academic performance. The integration of personalized learning paths and real-time feedback makes learning more interactive and adaptive. These findings highlight the need to design future mobile learning apps that prioritize accessibility and adaptability.