EDGE COMPUTING
REDEFINING THE EDGE: BUILDING DATA CENTRES FOR THE AI AGE Niklas Lindqvist, Nordic General Manager at Onnec, outlines the design principles that ensure edge facilities can meet rising AI-driven performance and efficiency demands. Artificial intelligence is no longer an idea for the future; it’s changing how businesses operate right now. As generative and agent-based AI systems grow in capability, organisations are rethinking how they store and process data. But while software is evolving fast, infrastructure is under pressure to keep up. The demand for compute power is soaring, putting strain on existing data centres. Edge computing is becoming a key solution to handling this growing need. Yet, building more edge data centres isn’t enough. To deliver the low latency, high bandwidth, and consistent performance that AI requires, edge data centres must be carefully designed from the start. Power, cooling, and cabling need to work together as part of one holistic system. Getting that balance right is what will make these facilities reliable, efficient, and ready for the future.
AI’S GROWING IMPACT AI is driving huge increases in compute demand across industries such as healthcare, logistics, and financial services. McKinsey expects global data centre capacity to grow by around 22% a year until 2030, with AI responsible for about 70% of that demand.
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Edge data centres are at the heart of this shift. Their physical proximity to users and devices helps reduce latency and improve bandwidth, making them ideal for supporting AI applications. The global edge market is projected to reach over $300 billion (£227.7 billion) by 2026, more than double its 2020 value. But this growth can only be sustained with solid design principles focused on three essential areas: power, cooling, and cabling. These three areas are tightly interconnected. As AI workloads drive up energy consumption, managing heat becomes a critical challenge. High-density cabling and heavy power demands can create hotspots that compromise both performance and reliability. Liquid cooling is increasingly favoured, providing greater efficiency than conventional air systems. At the same time, optimising power delivery – including integrating renewable sources and reusing energy – helps lower costs, supports sustainability targets, and reduces strain on local grids.
DESIGNING FOR THE AI EDGE Building an AI-ready edge data centre starts with understanding the IT load. Different AI models and applications place very different
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