AT&T recently signed a multi-year agreement exceeding $3 billion with Corning to procure fiber and cable for its nationwide broadband buildout of 60 million locations by 2030 – a core pipeline linking end-users, edge nodes, and large-scale data centers. In addition, fiber-infrastructure specialist Zayo recently told RCRTech that AI factories are redrawing the map for long-haul connectivity, also signing with Corning to add 15,000 new route miles by 2030, about 8,000 of which will be built in direct collaboration with Nvidia.

The convergence of telecom and AI infrastructure reflects a direct link between network connectivity and AI performance. Data center operators and telcos are distinct in their capabilities, but increasingly overlapping, with high-performance computing merging with distributed network architectures. As the AI industry pivots from training to inference, AI workloads will have to seamlessly move from massive central data centers down to regional edge nodes and across telco fiber lines. This will further push a convergence of data centers’ centralized “scale-up” capabilities with telcos’ hyper-distributed “scale-out” routing capabilities.

Additionally, as you’ll see in our “top story” below, AI applications will increasingly require ultra-low latency, reliability, and autonomous network operations, which will further deepen the relationship between the AI and telco industries.