The escalation of urbanization has resulted in a surge in vehicle numbers, exacerbating the challenge of parking space management in cities. This paper proposes an innovative approach utilizing Artificial Intelligence (AI) to address this issue. Our system amalgamates computer vision, machine learning, and data analytics to tackle aspects like real-time occupancy detection, predictive analytics, and parking allocation optimization. We delineate the system architecture; discuss employed algorithms, and present experimental results showcasing the efficacy and scalability of our approach. Our findings indicate that AI integration can significantly enhance parking space utilization, alleviate congestion, and improve urban mobility.