This chapter examines the increasingly important concepts of patient-centered care and clinical safety in the context of artificial intelligence (AI) technologies in healthcare services. First, the fundamental principles of the patient-centered care approach and the role of clinical safety in healthcare quality are explained; subsequently, the transformative impact of AI in these areas is evaluated from both theoretical and practical perspectives. In particular, the contributions of AI applications such as machine learning, big data analytics, natural language processing, and clinical decision support systems to the development of personalized care, the early identification of clinical risks, the reduction of medical errors, and the improvement of patient outcomes are discussed. The chapter also addresses the role of intelligent patient monitoring systems, early warning mechanisms, and data-driven decision-making processes in enhancing clinical safety, drawing on current research findings. Furthermore, ethical and managerial issues arising from the integration of AI applications into healthcare systems including data privacy, ethical responsibility, algorithmic bias, transparency, and human oversight are comprehensively discussed. In conclusion, the chapter provides a holistic evaluation of the opportunities and challenges associated with the use of AI in patient-centered care and clinical safety, offering a comprehensive framework for the future of healthcare services.