The AI Buildout
How Data Center and Network Providers Plan to Capitalize on the AI Revolution
Regional Concentration
Est. Global Spend Share 2025–2030
Market leader sustained by U.S. hyperscalers.
Projected CAGR of 22%–32%.
The AI Buildout is Underway, But its Foundation is Stuck in the Past
Every layer of the AI stack is being infused with intelligence and agility—except for the network.
It remains a static utility, disconnected from the dynamic demands above it.
Data Center (DC)
Focus: Land, GW-scale shells, advanced liquid cooling infrastructure
GPU Accelerators
Focus: High-density GPUs, TPUs, and AI-optimized servers.
Power
Focus: Dedicated on-site solar, nuclear (SMRs), and grid-scale storage for 24/7 AI ops
THE NETWORK (Fiber Infrastructure)
The network operates as a static utility—disconnected from the dynamic Intelligence Layer above.
To realize a full return on the massive capital invested in GW-scale data centers, power, and GPUs, operators must bridge the 'agility gap' with a NaaS strategy; unless network provisioning matches the minute-by-minute velocity of the cloud, these multi-billion dollar assets will remain underutilized and their ROI permanently sub-optimal.
Network as a Service for AI
Our Mission: We provide the agile network intelligence required for operators to move beyond commodity connectivity and become the essential, high-margin fabric connecting AI innovators to the resources they need.
Operator Insights: The Need for AI Agility
Zayo DynamicLink: The New Portal to NEOCloud, Built on InsidePacket NaaS
The Economics of NaaS
We analyzed the TCO of traditional networking vs. Network-as-a-Service for AI clusters. See the data behind the efficiency.
Data Sources
×- Global AI Spend: McKinsey, Gartner
- Compute Hardware: IDC, IoT Analytics
- Networking: MarketsandMarkets
- Energy: Gartner, Deloitte