Ciena survey: 90% of service providers see AI network services as key revenue driver
- 90% of service providers expect high-capacity AI network services to drive revenue growth
- 88% cite urgent need for optical network upgrades to support AI SLAs
- 96% expect MOFN services to generate revenue from distributed AI compute clusters
- 44% plan to use revenue-sharing models for GPU-as-a-Service opportunities

*this image is generated using AI for illustrative purposes only.
A new Ciena survey reveals that 90% of service providers expect high-capacity AI-driven network services to be a primary driver of revenue growth over the next three to five years.
The research, conducted by Censuswide among more than 1,200 telecom, wholesale, and regional service provider experts across 12 countries between July 13 and July 23, 2026, highlights a strong sense of urgency regarding infrastructure readiness. While 56% of respondents identify AI connectivity as their primary source of net-new revenue, 88% report a critical or high urgency for optical network upgrades to support premium enterprise AI service level agreements (SLAs).
Infrastructure Urgency vs. Revenue Opportunity
The data indicates a divergence between revenue optimism and infrastructure preparedness. Nearly half (48%) of respondents believe upgrades are critical, with 39% stating they are needed within the next 12-18 months. Only 11% believe routine upgrades will suffice. Advanced network automation, including agentic AI, is viewed as essential by 96% of respondents to capitalize on these opportunities.
Key Revenue Drivers
Service providers identified several specific areas where AI is reshaping revenue streams:
- Managed Optical Fiber Network (MOFN): 96% expect MOFN services to generate revenue from connecting distributed AI compute clusters within three years. 51% identify MOFN as their primary vehicle for delivering data center interconnect (DCI) services.
- AI Inference: 49% believe growth in AI inference data centers will create new revenue opportunities by increasing demand for DCI services.
- GPU-as-a-Service: 94% view strategic partnerships with cloud and neocloud providers as essential. Among those surveyed, 44% plan to adopt revenue-sharing models as their primary go-to-market strategy.
- Network Edge: 39% expect edge-hosted services, such as edge compute and localized AI inference, to drive more than 20% of enterprise revenue within three years. 88% expect it to drive at least 10%.
- Physical AI: 60% expect physical AI ecosystems, including industrial robotics, to account for more than 15% of total enterprise AI revenue within five years.
- Consumer AI: 95% believe immersive and AI-driven entertainment will contribute to new revenue streams in the next three years. 29% named AI wearables and personal devices as the leading consumer hardware category expected to drive premium service revenue.
Shifting Priorities: Reliability and Security
Beyond bandwidth, the survey highlights a shift toward reliability and security as monetization drivers. 35% of service providers identify network consistency, including guaranteed performance stability and low jitter, as the top opportunity for premium offerings. This reflects the critical nature of AI workloads to business processes.
Hyperscaler scale-across demand is also emerging as a substantial contributor to wholesale revenue growth, with 95% of respondents citing its importance. As power constraints limit single-campus data center expansion, distributed synchronous training requires ultra-high-speed connections reaching tens of petabits-per-second.
Security remains a top priority, with 51% of respondents stating they have launched or expect to launch commercial quantum-safe encryption services within 12 months. Another 48% are in early development stages. Advanced physical and cyber security capabilities were cited as the leading commercial driver of sovereign network infrastructure.
What the Numbers Show
The survey data reveals a clear dependency on partnership models for emerging AI services. While 94% of providers view partnerships with cloud and neocloud entities as essential for GPU-as-a-Service success, nearly half (44%) plan to rely specifically on revenue-sharing models. This suggests that service providers are positioning themselves as infrastructure enablers rather than sole asset owners in the high-capacity AI ecosystem.
Brodie Gage, Chief Product and Technology Officer at Ciena, stated that service providers are approaching AI with both optimism and urgency. He noted that success will depend on having the network foundation to support new performance demands.
How will the high urgency for optical network upgrades impact capital expenditure forecasts for telecom providers in the 2027-2028 fiscal years?
What specific regulatory or standardization challenges might hinder the widespread adoption of quantum-safe encryption services within the next 12 months?
Could the shift toward revenue-sharing models for GPU-as-a-Service erode profit margins for traditional service providers compared to asset-heavy competitors?

































