Hyperscalers (AWS, Google, Microsoft, Meta/FB) now dominate global subsea cable capacity. Their share of total international bandwidth has surged from negligible levels in 2010 to approximately 75% today. According to data from TeleGeography, hyperscalers are participating in over two-thirds of all planned submarine cable deployments, with Google alone anchoring eight new systems in the Asia-Pacific (APAC) region.  Despite this shift, traditional telecommunications operators remain critical to the subsea ecosystem.

Tier-1 telecom carriers provide the deep terrestrial reach and last-mile connectivity that both regional service providers and large content providers require to access edge markets. However, those network operators must increasingly architect their Wide Area Network (WAN) and long-haul transport infrastructure to integrate seamlessly with these massive hyperscale topologies.

Brian Washburn, Chief Analyst at Omdia’s Telco B2B Solutions Intelligence Service, notes that carriers face intensifying pressure to align their infrastructure with hyperscaler technical requirements. To achieve complete architectural control and establish fully isolated private networks, hyperscalers frequently seek to deploy proprietary optical transport equipment directly within carrier landing stations and co-location facilities.  This shift toward self-contained infrastructure creates visibility challenges for the industry. Washburn noted Google’s extensive transpacific cable network as a primary example. Because this hyperscaler traffic is routed over fully private, dark fiber subsea segments, it remains entirely invisible to carrier networks and traditional traffic-modeling metrics, rendering these massive data volumes completely opaque.

From a macro perspective, the deployment of next-generation physical infrastructure is increasingly tied to the rollout of raw, rack-scale data center capacity to support emerging AI workloads. Matt Walker, Chief Analyst at MTN Consulting, indicates that while Tier-1 US operators anticipate near-term traffic growth from centralized AI training models, they maintain a cautious, wait-and-see outlook regarding long-term network demand and the broader monetization of distributed inference at the edge.  “With agentic, the potential for rapid growth in unexpected parts of the network is real, and it’s not clear how to plan for this,” he said. Operators are worried they will be stuck with the network costs to support “these pricey new AI-enabled services,” he also noted.  Telco’s lack of visibility becomes a problem here. Walker stated in his research report:  “The industry is flying partially blind. No comprehensive public study of AI traffic volumes, patterns, or growth exists. Nokia, Ericsson, and a handful of others have made partial contributions, but hyperscalers don’t share traffic data. For an industry spending over $600 billion in capex this year, this is a significant planning liability.”