Large language models (LLMs) have dramatically transformed the field of natural language processing (NLP) by producing human-like text and demonstrating remarkable versatility across tasks. However, as these models become more pervasive, there is a growing need for personalization and human-context integration to make AI outputs more relevant, empathetic, and ethically aligned—supporting the development of human-centered AI (HCAI) systems. This chapter discusses the core concepts behind AI personalization, explains how human context shapes personalized interactions, and examines the technical and ethical implications of adopting personalized LLMs in diverse domains such as customer service, healthcare, and education. By exploring cutting-edge techniques and case studies, we illustrate how personalization can improve user satisfaction, trust, and the overall effectiveness of AI systems. Finally, the chapter addresses the challenges of maintaining privacy and mitigating bias and looks ahead to the future of human-centered, ethically responsible AI.