The integration of Generative Artificial Intelligence (GAI) into Massive Open Online Courses (MOOCs) represents a transformative shift in virtual schooling, notably enhancing personalization, engagement, and studying outcomes. This comprehensive literature review examines the position of GAI in optimizing MOOCs, emphasizing its packages in adaptive studying pathways, real-time personalized feedback, and intelligent evaluation systems. By leveraging large language fashions (LLMs) and statistics-driven insights, GAI allows dynamic content technology, customized quizzes, and automatic educational help, tailoring instructional experiences to individual rookies’ wishes. Despite its capability, the adoption of GAI in MOOCs increases crucial challenges, including moral worries, privacy dangers, algorithmic biases, and the integrity of AI-generated exams. Additionally, the shortage of clean regulatory frameworks affords limitations to ensuring transparency, equity, and responsible AI deployment in education. This overview identifies key study gaps and future guidelines, focusing on GAI’s sustainable and equitable integration in MOOCs to foster inclusive and robust virtual learning environments. By addressing these challenges, GAI can redefine online schooling, making MOOCs more excellent, interactive, private-sized, and accessible for numerous international novices. The findings presented in this look at function as a roadmap for researchers, educators, and policymakers seeking to harness the strength of GAI in the continuous evolution of era-more advantageous mastering environments.