Blog: Designing AI infrastructure for change.

London,  UK - 03. 07. 2026

AI is changing the shape of infrastructure demand

The growth of AI is driving a shift towards larger, more power-dense environments. Facilities that once measured capacity in tens of megawatts are giving way to campuses requiring hundreds of megawatts, while rack densities continue to rise.

These changes are prompting operators to rethink how infrastructure is designed. Supporting AI applications requires environments that can accommodate new hardware platforms, shifting compute requirements and new approaches to cooling.

As a result, technologies such as liquid cooling, modular architectures, alternative power sources and more dynamic interaction with energy networks are receiving increased attention, with each addressing different aspects of the challenge.

High-density computing changes infrastructure design

While AI is increasing demand for power, higher-density computing is also creating opportunities to improve efficiency.

Modern GPU systems deliver significantly more performance for compute-intensive applications, enabling organisations to make better use of power, space and materials. Higher-density environments can also reduce the amount of physical infrastructure required to achieve comparable results.

This places a premium on efficient capacity planning and avoiding unnecessary overbuilding.

Interconnected energy systems and data centers

Growing compute requirements are changing the relationship between data centers and the grid. As AI deployments expand, operators are exploring new ways to access and manage power.

Demand response programmes allow some facilities to adjust workloads or switch to on-site resources during periods of peak demand. Meanwhile, advances in battery storage, alternative fuels and small modular reactors are creating additional pathways to support future growth.

Utilities, grid operators and infrastructure providers are also adapting to increasing pressure on energy networks, bringing digital and energy infrastructure into closer alignment.

Cooling strategies are becoming more specialised

Higher rack densities are changing how heat is managed in data centers. AI clusters create very different thermal profiles, requiring a broader mix of cooling strategies.

Direct liquid cooling is attracting growing interest because it transfers heat efficiently in high-density environments. Closed-loop systems are also helping operators improve water efficiency while maintaining performance.

As hardware and applications diversify, cooling designs are becoming more tailored to specific environments.

Building the ecosystem

Supporting AI at scale requires closer coordination across the wider infrastructure ecosystem. Equipment manufacturers are working more closely with operators, while utilities are developing new approaches to grid management. Industry groups are also advancing standards that can help accelerate adoption and improve interoperability.

Shared standards and closer collaboration can simplify the introduction of new technologies and improve interoperability across the industry.

Built for long-term performance

Supporting AI workloads requires infrastructure capable of delivering high-density computing while maintaining consistent operational performance over time. That means designing facilities capable of supporting new hardware platforms, evolving cooling technologies and higher power densities.

For nearly two decades, Verne has focused on building and operating infrastructure across the Nordics and Northern Europe. That experience has reinforced the importance of engineering discipline, efficient operations and infrastructure designed for reliability and operational resilience.

Those principles continue to underpin the infrastructure we deliver across the region.

You can read Chapter 11 here and the full book is available on Amazon here.