Cyber-Physical Systems represent a transformative technological paradigm, seamlessly integrating computational intelligence with physical processes to revolutionize industries and societal functions. This paper explores the pivotal role of Artificial Intelligence (AI) in enhancing CPS capabilities, enabling autonomy, adaptability, and resilience across diverse applications such as smart manufacturing, autonomous vehicles, and healthcare monitoring. Key focus areas include AI-driven sensor fusion for advanced environmental perception, real-time adaptive control mechanisms for optimal system performance, and predictive analytics for proactive maintenance and fault detection. Furthermore, the integration of machine learning techniques, including deep learning and reinforcement learning, is highlighted for enabling CPS to navigate complex, dynamic environments with exceptional precision. The paper critically examines challenges in AI-CPS convergence, such as ensuring system reliability, fortifying cybersecurity, and addressing ethical dilemmas in autonomous decision-making. By synthesizing cutting-edge research and real-world case studies, this paper elucidates how AI is reshaping CPS design and functionality. Finally, it anticipates future trends and potential breakthroughs at the intersection of AI and CPS, offering profound insights into the evolution of intelligent, interconnected infrastructures that will redefine societal norms.