The purpose of this research was to provide a comprehensive understanding of how AI can be integrated into ODL to improve student engagement and educational outcomes. Based on a semi-structured narrative literature review, the findings indicate that AI technologies offer significant promise in transforming ODL by providing personalized tutoring, adaptive learning pathways, and customized support aligned with the needs of individual students. AI can analyze student performance data to identify learning gaps, recommend tailored resources, and continuously monitor progress, thus enhancing student engagement and success. However, it also shares limitations and challenges, such as ethical considerations, implementation challenges, and pedagogical implications. The research recommends integrating AI technologies into ODL frameworks, establishing ethical guidelines, and focusing on inclusive and equitable AI applications. Additionally, it suggests designing pedagogies and curricula that support the inclusion of AI for personalized learning. This research is theoretical and descriptive in nature, and further empirical research is needed to explore the long-term impact of AI-driven personalized learning to develop best practices for implementation. The chapter concludes that the integration of AI in ODL holds the potential to move beyond the traditional mass education models, offering individualized and responsive learning experiences that ensure the relevance and effectiveness of ODL institutions in future.