Metro Connect 2027 agenda

As AI workloads become larger, more distributed, and increasingly performance-sensitive, the network is emerging as a critical determinant of data center capability and competitiveness. Traditional architectures are being pushed to their limits by the demands of AI training and inference, requiring new approaches to scalability, latency, bandwidth, and power efficiency. This panel will examine how data center networks must evolve to support the next generation of AI infrastructure, exploring the technologies, architectures, and operational strategies that will underpin the AI backbone of the future. ' What network architecture innovations are needed to support large-scale AI training and inference workloads? ' How are operators balancing performance, scalability, resilience, and energy efficiency as AI demand accelerates? ' What role will emerging technologies such as high-speed interconnects, optical networking, and distributed AI infrastructure play in shaping the next generation of data center networks?