Alex Brew, Regional Director, Northern Europe at Vertiv, shares how AI is transforming data centre imperatives.

The rapid acceleration of interest in AI, and accelerated compute, is redefining the data centre landscape. The industry was previously predicated on providing stable digital infrastructure – but in the AI era, the focus is shifting to raw compute performance. AI has the potential to revolutionise industries from healthcare to finance and almost everything in-between; as that shift occurs, the demand on data centres to keep pace will increase. The International Energy Agency (IEA) estimates that global data centre demand could double by 2026, driven in large part by the power-hungry nature of AI models, particularly generative AI. 

From stability to agility

Traditionally, data centres were designed for stability, focusing on consistent uptime and reliable performance for predictable workloads. This model worked well for traditional IT operations but threatens to fall short in the AI era, where workloads are highly variable and resource-intensive. Training large language models (LLMs) require immense computational power and energy, while inference tasks can fluctuate based on real-time data demands. To adapt, data centres must embrace a more agile infrastructure.

Enhancing energy efficiency

The rising energy consumption associated with AI workloads is not just an operational challenge but also an environmental concern. Data centres are already significant consumers of electricity, and the projected doubling of energy use by 2026 will place even greater strain on both operators and the grid. This makes energy efficiency a top priority for the industry.

Innovative cooling solutions are becoming essential as traditional air-cooling systems struggle to keep up with the heat generated by high-density computing environments. Although air-cooling will be part of the infrastructure for some time to come, direct-to-chip liquid cooling technologies enable  data centres to maintain optimal temperatures without compromising performance.

According to industry analyst Dell’Oro Group, the market for liquid cooling could grow to more than $15 billion over the next five years. Additionally, integrating renewable energy sources and battery energy storage systems (BESS) can help mitigate the environmental impact while providing a reliable power supply during peak demands.

Strategic investments in infrastructure

As AI continues to evolve, so must the infrastructure that supports it. This requires strategic investments not only in physical hardware but also in management systems that can optimise performance and energy use. AI-driven automation within data centres can play a pivotal role, enabling predictive maintenance, dynamic resource allocation, and even automated responses to security threats.

Edge computing also has a role to play in an AI growth. By processing data closer to its source, edge data centres can significantly reduce latency and bandwidth usage, which is crucial for applications like autonomous vehicles and smart cities. This distributed approach potentially allows for more efficient processing of AI workloads, reducing the burden on networks and centralised data centres.

Collaboration across the ecosystem

The future of AI-driven data centres will be shaped by collaboration across the technology ecosystem. Operators, hardware manufacturers, software developers, and AI researchers must work together to develop solutions that meet the unique demands of AI. This collaborative approach is essential for driving innovation and ensuring that data centres can support the next generation of AI applications. For example, the integration of AI-specific processors and accelerators requires close coordination between hardware manufacturers and data centre operators.

There is also an emerging need to develop circular economies in AI data centres. Liquid cooling systems can also be integrated with heat reuse strategies, where the excess heat generated by AI workloads is captured and repurposed for other uses, such as heating buildings or supporting industrial processes. This approach not only leverages energy resources more efficiently but also contributes to the overall sustainability of the data centre, aligning with broader environmental goals.

A new role for data centres

As we navigate this new era of digital transformation, data centre operators are seeing their imperatives shift; the focus on resilient service provision to support digital growth, is making way for a new focus on supporting the compute performance to drive AI adoption. By investing in agile, energy-efficient infrastructure, and fostering collaboration across the ecosystem, data centres can position themselves at the heart of this transformation. In doing so, they will not only support today’s AI applications but also pave the way for future innovation.