Dell SVP Forecasts AI PC Surge as Data Centre Demands Shift
Enterprise adoption of AI reached record levels in 2024, driven by the emergence of generative AI tools. Now technology providers are focusing on the hardware required to run these applications at scale.
The shift towards AI-powered computing requires significant changes to enterprise infrastructure, from desktop computers to data centres. Companies face decisions about upgrading their technology stack while managing energy consumption and environmental impact.
These changes come as businesses move from experimental AI projects to full implementation. The transition raises questions about how organisations will process increasing volumes of data while maintaining security and controlling costs.
Organisations that fail to adopt the right AI strategy and architecture will be at a disadvantage
Dell Technologies expects 2025 to mark a turning point for AI adoption in UK enterprises as businesses move from testing to implementation of AI systems.
According to Steve Young, UK SVP and Managing Director at Dell Technologies, 70% of UK companies have achieved returns on investment from generative AI, following a year of experimentation with generative AI tools in 2024. “For many, the test-and-learn phase is already starting to pay off,” he says.
Dell sees healthcare, education, government and retail sectors as primary targets for AI implementation. “The focus should shift to developing tailored, scalable AI applications that solve current challenges while also positioning companies for future opportunities,” Steve says.
2025 to see rise of AI PC adoption
Dell predicts AI PC adoption will reshape workplace computing. Steve forecasts three factors will drive adoption of PCs with dedicated AI processing capabilities in 2025. The shift comes as Microsoft's Windows 10 operating system reaches end of support, forcing businesses to upgrade hardware to meet Windows 11 requirements.
Steve says data processing will increasingly move from centralised data centres to the edge – devices at the point where data is created and used. AI PCs incorporate neural processing units (NPUs), specialised chips that handle AI workloads directly on the device.
“With AI PCs, data can be processed directly on the device to drive real-time insight, potentially reducing cost and allaying security considerations,” Steve says.
The market for AI-capable processors is expanding. Dell expects more manufacturers to offer central processing units (CPUs), graphics processing units (GPUs) and NPUs optimised for AI workloads. The company projects that every PC will include a dedicated AI accelerator by 2030.
Dell offers AI infrastructure framework to support transition
Data centre infrastructure faces AI-driven transformation. By 2026, AI workloads will represent over half of data centre processing requirements. Up to 90% of AI processing will focus on inference – using trained AI models to make decisions – by 2025.
This shift requires new approaches to data infrastructure. Traditional data centres with fixed ratios of computing, storage and networking will give way to disaggregated architectures where these components can scale independently.
Dell has developed its AI Factory framework to help organisations integrate AI across different infrastructure types. The system aims to simplify deployment of AI applications while maintaining flexibility.
Environmental impact becomes priority as AI adoption grows The UK government has designated data centres as critical national infrastructure and aims to reduce planning restrictions. This expansion makes environmental impact a priority, with government targets requiring an 81% cut in emissions by 2035.
The focus should shift to developing tailored, scalable AI applications that solve current challenges while also positioning companies for future opportunities.
Energy consumption from AI systems currently represents a small portion of IT power use, but this is expected to increase as adoption grows. Steve says organisations must focus on “‘right-sizing’ AI solutions, tailoring infrastructure to business needs, enhancing energy efficiency through observability and control, and using renewable energy for data centres.”
He also recommends organisations audit their current computing infrastructure to prepare for AI integration. This includes assessing PC fleets against future requirements and evaluating data centre capabilities.
“We’ll see traditional siloed data centres being replaced by disaggregated architectures, which allow computing, storage, and networking systems to scale independently,” Steve says. “Organisations that fail to adopt the right AI strategy and architecture will be at a disadvantage.”
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