The global shift toward digital education has highlighted the urgent need for personalized learning solutions that accommodate diverse linguistic and cultural backgrounds. In multilingual education systems, where learners often face barriers related to language proficiency and curriculum accessibility, Artificial Intelligence (AI) has emerged as a transformative force. By leveraging machine learning, natural language processing, and adaptive learning algorithms, AI can design individualized learning pathways tailored to each student's language skills, cognitive preferences, and academic goals. This paper explores the foundational technologies behind AI-driven personalization in e-learning, focusing on content recommendation, real-time translation, and learning analytics. It presents use cases in formal education, adult learning, and inclusive education for marginalized linguistic communities. Case studies from global platforms and regional initiatives illustrate the effectiveness of AI in bridging language gaps and improving learning outcomes. Ethical considerations such as algorithmic bias, data privacy, and equity are critically examined. The paper also identifies challenges including limited language resources, contextual understanding, and integration with existing educational systems. Future directions include AI-supported multilingual tutoring, cross-cultural pedagogy, and low-resource language inclusion. AI-powered personalization promises a future where learners from diverse linguistic backgrounds can access equitable, engaging, and effective education