With the rise of artificial intelligence and machine learning reshaping the data centre landscape, Darren Watkins, Chief Revenue Officer at VIRTUS Data Centres, considers the challenges ahead and how the sector can ensure scalability and sustainability.

In the world of technology, data centres have always been IT hubs of innovation. However, they’re now facing a new critical challenge where they need to do more than provide the essential network and infrastructure supporting data storage, management and cloud services in an always-on manner. The rapid rise of artificial intelligence (AI) has made this requirement even more critical, and data centres must now be flexible, creative and collaborative to keep pace with this changing landscape.

The boom in AI and machine learning (ML), coupled with continued growth in cloud and enterprise workloads, demands a re-evaluation of data centre strategies, designed in partnership by operators and customers. Beyond proximity, power and speed, success now necessitates foresight – solving customer challenges before they arise. This includes managing sustainable power at scale, implementing designs that support rapid and scalable AI deployments and resonate with operational needs, whilst consciously aligning with values that benefit the data centre provider, the customer and wider society responsibilities.

Redefining location dynamics for scalability

In the past, network technology decisions were often about reducing data processing speeds, dictating that facilities were strategically placed to minimise latency. But now, with AI and ML taking centre stage, these priorities are shifting. Unlike tasks sensitive to delays, the new workloads don’t always need data centres optimised for low-latency. This change challenges the perceived wisdom about where data centres should be located. Instead, there’s a growing preference for bigger campuses with 200-500 MW of power and access to renewable energy.

This shift isn’t about lessening the importance of low latency – it’s about recognising the evolving needs of integrating AI and ML. The move towards larger campuses isn’t just because these tasks aren’t as sensitive to network speeds, often it is a strategic decision that acknowledges the different cost dynamics involved; bigger campuses generally offer more efficiency for providers and customers alike. This bold move goes against the traditional thinking in the industry, suggesting that focusing on scale rather than proximity can lead to more efficient and sustainable results.

Redoubling sustainability efforts

It’s long been understood that data centres have a crucial role to play in building a more sustainable environment. And this imperative is further underscored by the recognition of the important role energy efficiency plays in the ongoing transformation of data centre operations. The move towards larger campuses must align seamlessly with the imperative to reduce environmental impact. The emphasis on sustainability is not just a buzzword but a strategic acknowledgment that data centres, powered by renewable energy, are integral to a future where efficiency and environmental consciousness go hand-in-hand.

While some may consider access to power, water, and connectivity traditional requirements from a customer’s perspective that will remain unchanged, data centre providers must continue work hard to innovate to lower Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) – and in turn, reduce their reliance on diesel generators. Sourcing only 100% renewable energy and Power Purchase Agreements (PPAs) to use dedicated solar and wind farms to power data centres are all critical initiatives which the most sustainable data centre providers are ensuring are embraced.

Flexibility in design: the new imperative for AI

In the fast-paced evolution of data centre technologies, achieving ‘AI readiness’ goes beyond technological prowess – it hinges on the imperative of early engagement with those customers who need AI ready infrastructure. This strategic engagement of provider and customer not only ensures a symbiotic relationship, but also serves as the linchpin for developing a truly flexible and customised infrastructure that can seamlessly evolve with the fast-growing and ever-changing technological landscape which AI requirements are driving.

The essence of this early engagement model transcends conventional collaboration. It is a dynamic and continuous dialogue that lays the groundwork for what can be termed as a ‘built-to-suit’ approach. Unlike static solutions, this approach is inherently responsive, recognising that the needs and challenges of customers are not all known at the outset, but rather subject to constant evolution and refinement.

Defining the future: megascale and the edge

As AI reshapes customers’ data centre needs, discussions arise about the naming conventions for the next generation of facilities. Terms like hyperscale 2.0, megascale, and gigascale are under consideration. However, the label “hyperscale” extends beyond physical size to now reflect specific customer requirements.

Reframing it as “megascale campuses to host hyperscale customers” better captures the ongoing industry shifts. Despite the terminology, the shared challenge remains – meeting the substantial capacity demands posed by AI. European hyperscale facilities face limitations in addressing the expanding AI market, suggesting megascale campuses as a potential solution.

Meanwhile, edge computing maintains its relevance beyond megascale campuses. With AI/ML adoption, demand for edge solutions rises, enabling full system integration. While megascale campuses may house the core AI components, edge solutions in cities ensure seamless connectivity. Edge computing remains crucial for latency-sensitive applications like live broadcasts, and cost-effectively deliver low-latency solutions such as content distribution networks and streamlining processes like iOS upgrades for global audiences.

Ready for AI

As we navigate these transformative trends, one thing becomes abundantly clear – the data centre landscape is undergoing a significant evolution. The integration of AI/ML workloads, the redefinition of scalability, and the strategic development of ‘AI-ready megascale campuses’ collectively mark a new chapter in the story of data centres. This is not merely about keeping up with demand; it’s about steering our course towards a data-driven future that is as dynamic as it is sustainable.

Providers need to remain committed to delivering data centres that underpin the ever-growing data-driven digital economy, powering the information and applications that we all rely on day-to-day. The continued growth of AI (Statista predicts that the AI market will reach $305.9 billion in 2024 and show an annual growth rate of 15.83% resulting in a market volume of $738.8 by 2030) opens up exciting opportunities for providers to further explore design, construction and operational innovation and redefine what’s possible in the data centre industry, whilst ensuring commitment to operational excellence and sustainability.