Ciena, in partnership with Heavy Reading (now part of Omdia), recently conducted a global survey examining how AI applications and rising traffic are affecting metro and long-haul networks across communications service providers (CSPs)—spanning fixed, mobile, converged, and cable operators.
The Optical Transport Networks for AI report found that CSPs expect significant traffic demand from AI in their metro networks over the next three years, with 18% expecting AI to contribute more than half of their total metro network traffic, and nearly half (49%) expecting AI will exceed 30% of metro traffic. When it comes to long-haul traffic, CSPs have even higher expectations for AI. While just over half (52%) believe AI will exceed 30%, nearly one-third (29%) believe that AI will contribute more than half of long-haul traffic over the next three years.
“This research highlights the rapid rise of AI applications — from large-scale models to cloud AI services and edge-to-core workflows — that are set to become major drivers of both local and long-haul network traffic,” said Sterling Perrin, Sr. Principal Analyst, Heavy Reading – now part of Omdia. “For metro networks, where AI will compete with video, web, and IoT traffic, the projected growth is striking. With AI expected to take an even larger share of long-haul capacity within three years, it’s clear that AI data flows, including those used for training and inference, will put unprecedented demands on CSP networks.”
Connectivity services for AI traffic
The survey found that CSPs expect to play a much broader role in AI connectivity as the market matures, particularly in serving enterprise customers with high bandwidth wavelength services at 100G, 400G, and even 800G data rates.
- 50% of respondents ranked high-bandwidth wavelength services as top in a list of services expected to grow the most from AI over the next three years.
- By comparison, just 25% of respondents expect dark fiber to grow the most due to AI.
- 74% of CSPs expect enterprise customers to drive the most traffic growth on their networks over the next three years, ahead of hyperscalers and cloud providers.
Challenges to optical network readiness for AI
The survey indicates a broad mix of challenges standing in the way of taking advantage of the AI traffic boom. Globally, the top challenges include capex constraints (38%), go-to-market/business strategies (38%), and network management (32%).
While 16% of CSPs surveyed believe their optical networks are “very ready” for AI, most recognize there is still work to be done when it comes to their optical networks’ readiness to support AI network demands. 39% report their networks are “ready,” with “much of the network in place but still some work to do”, 40% reported that they are just “somewhat ready” with much work remaining, and 5% reported their optical networks are not ready at all.
The report is based on a custom survey of 77 CSPs, fielded globally by Informa TechTarget in February 2025. Read the full Optical Transport Networks for AI report here.
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