Abstract: The rapid advancement of large language models (LLMs) such as ChatGPT, Claude, and Gemini presents new opportunities for personalized education. These AI systems are capable of tailoring learning experiences, providing instant feedback, and supporting self-paced study. However, questions remain regarding their pedagogical effectiveness, ethical implications, and alignment with educational goals. This study explores the opportunities and challenges of integrating LLMs into personalized learning environments in higher education. Using a mixed-method approach that combines experimental use of LLM-based tutoring with surveys and interviews of students and educators, the research evaluates their impact on engagement, learning outcomes, and inclusivity. Findings are expected to contribute to the discourse on AI in education while supporting the United Nations’ Sustainable Development Goal 4 (Quality Education), particularly in promoting inclusive and equitable access to learning opportunities through emerging technologies.