F E A T U R E
AI’ s impact on data centre design
• AI workloads are growing nearly 20 % per year
• Training large language models requires 10 – 50 times more power than traditional cloud tasks
• Cooling demand can rise by 40 % in AI-optimised facilities
• AI scheduling tools reduce build delays by up to 25 %
• Predictive analytics lower downtime risk by 30 %
But energy supply is only part of what is essentially a design and delivery problem.
We need a radical new approach to data centre growth
Meeting soaring demand requires a new approach: data centres that can auto-scale capacity, reconfigure cooling and optimise onsite renewable energy sources – all in real time. virtually mock up entire halls, simulating airflow, thermal loads and failure scenarios before breaking ground.
Cloud data platforms bring engineers together within one integrated model, eliminating coordination issues and rework. AI-driven scheduling tools draw on previous projects to optimise construction sequencing, dynamically adjusting subcontractors’ deliveries and timetables to mitigate risk.
Predictive analytics, modular planning tools and sustainability simulators – layers of the digital twin – help ensure new data centres are smarter, more energy-efficient and environmentally responsible from day one. Depending on local conditions, some can even generate renewable energy onsite and feed excess power back to the grid.
What’ s changing is how the tech stacks together. It’ s now possible to access these disparate but complementary technologies via a single-window interface.
This agility is best exemplified by Brazilian company AP Consultoria e Projetos. With a unified tech stack, the engineering, procurement and construction( EPC) firm can now model, design and deliver complex capital projects in line with timeline and budgetary targets.
Using 3D design, it overlays laser scans of plants with customers’ engineering data to cut rework time by 29 % and reduce field trips by up to 90 %. Thanks to cloud-based data management, all
That means radically rethinking how we build this essential new infrastructure using digital-first, agile construction models.
Engineering is already digital-first. The once-novel technologies of the Fourth Industrial Revolution( Industry 4.0) have now become mainstream, with projects being handed over faster. Research shows a clear correlation between Industry 4.0 adoption and shorter construction cycles and lower resource capex.
This means data centres that come online quickly and are designed to accommodate future needs. Several technologies are behind the shift.
Digital blueprints, generative design AI and sustainability simulators
The launch of reference blueprints for data centres that can handle even NVIDIA’ s most powerful AI systems can save companies weeks or months of planning and design times( similar to the rise of modular design solutions).
Digital tools now accelerate every stage of engineering. Designs are vetted and executed using digital twins and generative design AI tools, so teams can
Nayef Bou Chaaya Vice President Middle East Africa and Turkey AVEVA
How unified visibility enables fitfor-purpose facilities
A unified operations centre is a system of systems that integrates real-time and historical data from different vendors into actionable dashboards built around KPIs such as power efficiency, utility costs and maintenance.
Using 3D templates, engineers from different companies can collaborate on the same virtual model, share feedback instantly and co-ordinate tasks and resource deployments in context.
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