The increasing complexity and scale of cyber threats have necessitated the adoption of advanced solutions beyond traditional network security mechanisms. Artificial Intelligence (AI) has emerged as a transformative technology for real-time threat detection and automated incident response, offering both speed and accuracy in identifying and mitigating risks. This paper explores how AI-driven approaches enhance network security through predictive analytics, anomaly detection, and adaptive defense mechanisms. Furthermore, it emphasizes the importance of incorporating sustainability in the design and deployment of AI-based security frameworks, ensuring that solutions are energy-efficient, scalable, and environmentally responsible. The integration of sustainability into cybersecurity strategies not only optimizes operational performance but also aligns with global green computing initiatives. Case studies and quantitative evaluations demonstrate the effectiveness of AI in reducing response time and minimizing resource consumption while maintaining robust security standards. This research contributes to the growing field of secure, intelligent, and sustainable network infrastructures.