AI For Core Network in 6G

This paper aims to explore the prominent role of artificial intelligence (AI) in shaping 6G core networks, addressing its AI-nativeness, automation, and security applications in broad terms. Vision, requirements, and key enablers of 6 G core architectures are analyzed, emphasizing AI-driven design principles for scalability, real-time inference, and energy efficiency aspects. By reviewing state-of-the-art AI techniques for core network functions, we spot significant challenges such as interoperability, energy efficiency, computational complexity, and standardization gaps. Our synthesis provides insight for academia and industry to further enhance AI-native 6 G core networks, balancing innovation with deployability in next-generation mobile systems.