Everyone wants to talk about GPUs. But the real bottlenecks in AI infrastructure? Power, delivery timelines and whether sites can actually support what’s being deployed. Great discussion at @Engineering_SES's roundtable with our CBDO & Co Founder, @CudoPete on what the UK data centre sector is now up against as AI demand accelerates. Because the challenge is no longer just getting access to compute. It’s getting infrastructure live, operational and scalable in the real world.

96.7% of UK organisations expect power availability to influence where AI workloads are deployed in future. The conversation around AI infrastructure is changing. For years, the focus was on GPUs. Today, organisations are increasingly grappling with a broader challenge: aligning land, power and compute quickly enough to support AI growth at scale. Land takes years. Power takes years. Compute evolves annually. Alignment is now the challenge. Explore the report today: cudocompute.com/land-power-c…

For years, AI infrastructure conversations have centred on GPUs. But the economics of AI are changing. Research from our industry report, Land. Power. Compute. found that long term power contracts, network and data transfer costs, and power availability now rank above GPU pricing as drivers of total AI compute cost. The question is no longer just whether you can access the GPUs you need. It's whether you can power them. In our latest blog, we explore why power is becoming one of the defining factors in the cost of AI at scale. Read more: cudocompute.com/blog/why-pow…

The AI conversation has spent years focused on chips. But securing GPUs is only part of the equation. In his latest article for @UniteAi, @HawkinsTech explores the growing attention being paid to energy availability, grid capacity and the infrastructure needed to support AI at scale. As demand continues to accelerate, these are becoming strategic considerations rather than operational ones. Read the full article today. unite.ai/ai-infrastructure-e…

Final day at Datacloud Global Congress 2026 by @BroadGroup_Intl . For @CudoPete and Michael Jones, the week has been less about the headlines and more about the conversations happening behind them. From AI infrastructure deployment and data centre capacity to power, operations and delivery, it's been valuable to hear first hand how organisations across the ecosystem are approaching the challenges and opportunities ahead. A huge thank you to everyone who took the time to meet with the team this week. It's been a great opportunity to reconnect with familiar faces, make new connections and exchange perspectives with the people building the infrastructure that will underpin the next generation of AI. Until next time, Cannes.

The AI race is increasingly being decided by physical infrastructure. Power. Land. Capacity. Delivery. That's why we're at Datacloud Global Congress this week. @CudoPete and Michael Jones are on the ground discussing the challenges and opportunities shaping the next generation of AI infrastructure. If you're in Cannes, let's talk.

As GPU clusters become denser and power requirements continue to increase, cooling is becoming a critical consideration in how AI infrastructure is designed, deployed and scaled. In our latest blog, we explore the technologies shaping the next generation of AI environments, from immersion cooling and direct liquid to chip systems through to advances in air cooling, and what they mean for performance, efficiency and future capacity planning. Because delivering AI infrastructure at scale is no longer just about compute. It's about managing the heat that comes with it. cudocompute.com/blog/cooling…

Everyone wants AI capacity. Fewer are talking about whether the infrastructure underneath it can actually keep up. You can secure GPUs in months. Power infrastructure can take years. Land, permits and grid access move on entirely different timelines. That mismatch is becoming one of the biggest blockers to AI deployment. Our Land. Power. Compute. report explores why AI infrastructure is no longer just a compute conversation. It’s a coordination challenge across physical infrastructure, energy and delivery. Read it today: cudocompute.com/land-power-c…

Cannes next. Our CBDO & Co-founder, @CudoPete and HPC Supply Manager, Mike Jones are heading to Datacloud Global Congress next week, joining the conversations shaping the future of AI infrastructure across Europe and beyond. As demand for AI capacity accelerates, the focus is shifting towards the realities behind deployment at scale, from power and density through to operational readiness and long term infrastructure strategy. If you’re attending Datacloud and want to talk GPU infrastructure, AI factories, sovereign capacity or scaling AI environments in production, catch up with the team on the ground.

Most people use AI every day. Very few understand the infrastructure behind it. That is exactly why initiatives like National Data Centre Day 2026 matter. As AI adoption accelerates, the conversation cannot stop at applications and models. The future of AI will also depend on the people designing, operating and scaling the infrastructure behind it. From power and cooling through to networks, compute and operations, this industry needs the next generation to understand what digital infrastructure actually is and why it matters. That is why CUDO Compute is proud to support National Data Centre Day and this year’s #BackToSchool initiative. Because the future of AI is not just built in code. It is built on infrastructure. And if we want the next generation to shape that future, we need to start bringing them into the conversation now.

The AI market is entering a new phase. One where infrastructure decisions are becoming business critical. Not just what GPUs are available, but where capacity can actually be deployed. Where power can be secured. Where density can be supported. Where environments can be delivered fast enough to keep pace with demand. The conversation around AI is maturing and infrastructure is now firmly part of that discussion. Land. Power. Compute explores the realities shaping the next era of AI deployment across land, energy and compute infrastructure. Read the report today: tinyurl.com/land-power-compu…

Two days at Data Centre LIVE and one thing became increasingly clear: The AI infrastructure conversation has fundamentally shifted. Across panels, meetings and conversations throughout the event, the same themes kept surfacing: Power constraints. Deployment timelines. Cooling. Density. Sovereignty. Operational readiness. Less conversation around simply securing GPUs. Far more conversation around whether infrastructure can actually support AI at scale. It mirrors one of the biggest findings from Land. Power. Compute.: AI is no longer constrained by algorithms alone. It’s increasingly constrained by the physical infrastructure required to deploy it. The industry is moving beyond compute procurement and into infrastructure reality. Land that can support development. Power that can sustain AI workloads. Infrastructure that can actually be delivered and operated at scale. Great to catch up with partners, peers and others across the ecosystem pushing these conversations forward. Want to dive deeper into the infrastructure realities shaping AI deployment? Read the full report today: tinyurl.com/land-power-compu…

AI infrastructure is becoming a physical delivery challenge as much as a technology one. In his latest piece for @electronicspec, our CEO, @HawkinsTech explores how power availability, planning constraints and infrastructure readiness are increasingly shaping the future of AI deployment in the UK. As demand for AI accelerates, the conversation is shifting beyond compute alone towards the realities of grid capacity, energy access and the infrastructure required to scale AI sustainably. The UK has the ambition. The next challenge is delivering the infrastructure to support it. You can read the full article here: electronicspecifier.com/prod…

The CUDO Compute team will be on the ground at Data Centre LIVE (@DataCentre_Mag) this week speaking with operators, partners and infrastructure leaders about the realities shaping AI infrastructure deployment today. As AI demand accelerates, the conversation is shifting far beyond GPUs alone. Power availability, grid readiness, cooling, delivery timelines and operational execution are now becoming the defining factors behind scalable AI infrastructure. Looking forward to the discussions ahead and catching up with partners, peers and others across the industry. If you’re attending, come say hello: Dean Fletcher Kir Devaser (@flowerpower_96) Mark Richman Michael Jones Mohamed A.

The AI infrastructure conversation has spent the last two years focused on GPUs. But the reality is, infrastructure strategy is increasingly being shaped long before hardware even arrives. Power availability. Grid certainty. Geopolitical stability. Land that can actually support deployment at scale. According to our Land. Power. Compute. report, 96% of infrastructure leaders have already adjusted infrastructure location strategy due to geopolitical or grid conditions. This is exactly why AI infrastructure can no longer be viewed as isolated layers of land, power and compute. They are now deeply interconnected strategic decisions that directly impact deployment timelines, operational resilience and long term scalability. The industry is moving beyond simply securing compute capacity. The focus is shifting towards securing deployable, sustainable and sovereign ready infrastructure. Read the full report today: tinyurl.com/land-power-compu…

Over the last two years, GPU access has dominated the AI conversation. Now, the industry is confronting a different challenge entirely: Can infrastructure keep pace with AI demand? Land. Power. Compute. Our latest report explores the physical realities now shaping AI deployment at scale, from power availability and grid constraints to permitting, cooling and long term infrastructure readiness. Built from insights gathered across 700 infrastructure leaders across the US, UK and Europe, the findings point to a market increasingly constrained not just by hardware, but by the systems required to support it. Some of the clearest findings: • Infrastructure now accounts for 71% of AI deployment cost pressures • GPU pricing ranked sixth among deployment cost drivers • 96% of organisations say geopolitical and infrastructure conditions are influencing deployment strategy • Power availability is increasingly shaping where AI infrastructure gets built The AI industry may have started as a software revolution. Scaling it is rapidly becoming an infrastructure challenge. Download the report today: tinyurl.com/land-power-compu…