Better, faster, simpler: Arelion’s AI networking advantage

The rise of AI is pushing connectivity’s limits, requiring lower-latency data transfer, resilient infrastructure and an expansive network footprint. Arelion has built our network to meet these demands for over three decades. With one of the world’s most extensive and scalable Internet backbones, we’re not just keeping pace; we’re setting the standard.

Whether supporting massive training models or enabling real-time inferencing globally, our dark fiber assets, 400G Ethernet capabilities and IP backbone uniquely position us to support the next era of AI.

AI use cases: what’s coming next

AI/ML workloads are scaling rapidly, with some experts estimating that data center capacity could triple by 2030 due to AI. Most headlines focus on model training, which is driven by hyperscalers and cloud data centers racing to provision power and GPUs to support generative applications.

Over time, AI workloads will shift from training systems operated by cloud hyperscalers and data centers to the network edge to enable inferencing. This functionality allows companies to leverage agentic AI to perform decision-making and reasoning functions across hybrid environments and in networking sites closer to end users.

The transition from generic generative models to specialized agentic and reasoning AI will dramatically reshape infrastructure and connectivity requirements. Infrastructure providers must not only support data capacities in AI models. They must also move this data efficiently between distributed nodes to ensure real-time responses to end-users at the edge. These inference workloads will demand proximity to users, ultra-low latency and massive scalability without compromising security, compliance or availability.

Challenges in a shifting market landscape

Traditional telecom operators are struggling with these evolutions. Some are exiting global connectivity altogether, while others are doubling down on local fiber or mobile services. For many in the telecom space, AI is a tool to enhance internal operations, not a business driver. This reality presents enterprises and hyperscalers with a quandary.

They need connectivity partners that are optimized for AI, not legacy networks hindered by consolidation and integration complexities. As AI proliferates, the need heightens for global, high-capacity networks purpose-built to move and process data at scale.

These optimizations become vital as many markets expand beyond historical hubs, like Northern Virginia, Frankfurt and London, to growing, lower-tier markets where land, power and fiber are more available, sustainable and cost-efficient.

Two core use cases, one scalable network

As we always have, we’re addressing both sides of the AI equation by focusing on what we do best:

1. Bringing data to the model
High-performance compute, training workloads and massive data capture demand wavelength services, dark fiber and managed optical networks at terabit scale. Our fiber backbone connects major data centers and clouds across North America, Central America, South America and Europe, with high-count fiber cables and ducts enabling high-availability access to one of the largest footprints in the industry.

With our infrastructure, enterprises and hyperscalers can secure dedicated capacity and scale confidently as they look to capitalize on AI’s business opportunities.

2. Distributing model outputs to the edge
When users interact with AI models through search, chat or real-time reasoning, they need high-performance connectivity to reach agents globally. Our IP backbone is ranked #1 worldwide, directly connecting to over 350 Points-of-Presence (PoPs) and the top 5 cloud providers across 128 countries through over 77,000 kilometers of fiber routes.

We enable Internet transit or dedicated connectivity with up to 400G capacities (and 800G on the horizon), offering built-in class-of-service options to handle massive, unpredictable traffic bursts and virtual backbone needs for inference and distribution.

Our strategic focus on simplicity, capacity and reach, backed by a decades-long commitment to organic expansion rather than patchwork networks, helps our customers avoid the complexity and fragmentation that can hamper successful AI implementation.

Ready for tomorrow’s AI requirements

From 1,000+ kilometer IP transmissions using 800G ZR+ optics to recent network expansions in Mexico and new builds in emerging markets, we’re preparing for a future where AI is everywhere, not just in the cloud.

As AI moves from centralized learning to distributed, reasoning-enabled inferencing, network infrastructure must keep pace. We’ve been preparing our backbone for these requirements since 1993. With future-proof capacity, a global footprint and reliable connectivity solutions specialized for AI workloads, we’re not just adapting to change. We’re enabling it.

Stay tuned for the next blog in this series, where we’ll explore our latest optical networking innovations and regional expansions across North America and Europe, with these strategic moves designed to power AI’s future at every level of the telecom ecosystem.

Johan Ottosson, VP Strategy & Product Management