The Growing Role of AI Infrastructure in Enterprise Transformation
On September 22 2024, in Liverpool, the Labour Party Conference featured a pivotal Data Centre Panel Session hosted by OpenUK’s Amanda Brock. Stelia’s Chief Commercial Officer, Dan Scarbrough, joined industry leaders to discuss the rapid evolution of AI infrastructure, the changing geography of data centre hubs, and the growing energy demands of modern AI workloads.
As enterprises accelerate their AI adoption, the conversation underscored a key reality: AI execution is now the primary challenge — not experimentation. Here are five critical takeaways that every enterprise should consider.
1. Exponential Growth in Computing Power
The industry is witnessing a step change in AI capabilities. Today’s NVIDIA GPUs are 4,000 times more powerful than their 2018 predecessors, enabling enterprises to train and deploy increasingly complex AI models. However, as models scale, so does the need for optimized infrastructure that ensures these powerful engines can actually operate efficiently in production environments. 
Stelia Insight: AI models are just the engines — infrastructure is the vehicle that makes execution possible. As compute intensity surges, businesses need a scalable, purpose-built AI infrastructure to avoid bottlenecks in production deployment.
2. The Shift in Data Centre Hubs
While Frankfurt, London, Amsterdam, and Paris (FLAP) have long dominated, a regional shift toward Scandinavia is underway. Lower energy costs and an abundance of renewable power make Nordic data centres increasingly attractive for enterprises seeking cost-effective AI scalability.
3. Skyrocketing Power Requirements & Efficiency Challenges
The power demands of AI infrastructure are reaching unprecedented levels. Some AI clusters now consume over 150 megawatts, with annual electricity costs exceeding $300 million. With energy efficiency becoming a business-critical issue, enterprises must rethink how they optimize infrastructure to sustain long-term AI scalability.
Stelia Insight: AI execution at scale demands more than just raw compute—it requires optimized GPU orchestration and real-time inference efficiency. Without a purpose-built infrastructure, power inefficiencies can become a major cost and performance bottleneck.
4. Multi-Modal AI is Reshaping Enterprise Data Strategies
AI is no longer just about text and structured data. The future is multi-modal—spanning audio, video, and sensor-based data. This shift will fundamentally transform how enterprises interact with, process, and extract insights from data, requiring an adaptable AI infrastructure layer that can handle diverse workloads efficiently.
5. Network Infrastructure Bottlenecks Could Limit AI Adoption
One of the most pressing challenges discussed was the fragility of existing network infrastructure. As AI applications demand ultra-low latency and high-bandwidth data mobility, many enterprises risk falling behind due to outdated digital infrastructure.
Stelia Insight: AI decision-making must be instant, not delayed. Eliminating latency bottlenecks through optimized data mobility platforms will define the next wave of enterprise AI execution.
The Future is Now: Preparing for AI-First Operations
The panel’s conclusion was clear: AI infrastructure is the defining factor separating leaders from laggards in the AI economy. Organisations that fail to modernise their compute, network, and energy strategies will struggle to keep pace with innovation.
Next Steps for Enterprise Leaders:
✔ Assess your AI infrastructure—Can it support the demands of real-time AI execution?
✔ Explore strategic data centre partnerships—Are you leveraging emerging hubs for cost and efficiency gains?
✔ Invest in scalable inference solutions—Can your infrastructure handle AI workloads at production scale?
As enterprises transition from AI experimentation to execution, those who take decisive action today will define the future of AI-driven business.
Want to learn more about optimizing AI infrastructure for real-time execution? Reach out at connect@stelia.ioto explore how Hyperband can accelerate your AI projects.
