AI Data Center
Power up your AI infrastructure
AI Data CenterTransform your AI data center with advanced infrastructure designed for high-performance computing, efficient workloads, and seamless scalability.
An AI data center delivers the high-performance computing required for today’s intelligent systems. It integrates powerful processors, scalable storage, and advanced cooling to run complex models efficiently. This setup enables faster analytics, smoother automation, and stronger digital capabilities across industries, supporting growing workloads and future innovation for businesses.
Role of Cooling Technologies in AI Data Centers
Cooling technologies play a vital role in AI data centers by managing the heat generated during intensive computing tasks. Efficient cooling ensures stable performance, prevents hardware failures, and supports continuous high-power workloads, helping systems operate reliably as data demands continue to increase and evolve for modern operations.
With Motivair, Schneider Electric leads in cooling
Motivair AcquisitionIn February 2025, Schneider Electric acquired a controlling stake in Motivair Corporation, reinforcing our commitment to delivering top-tier cooling solutions for the global data centre market. Together, we provide an end-to-end cooling portfolio—from Grid to Chip and Chip to Chiller—designed to meet the increasing demand for high-density computing.
Be the first to see how we’re solving today’s toughest AI energy challenges
Accelerated Innovation: AI-Ready Data Centre Solutions BroadcastDiscover the latest AI-ready innovations and energy solutions, as we continue to be your trusted partner.
Discover how we empower your data centre with available, decarbonised, and optimised energy solutions for the AI era.
- Streamline energy sourcing with our consulting and procurement services.
- Add onsite power generation systems designed for speed to market, reliability and resilience, and sustainability.
- Manage all of your power sources for optimised availability and decarbonisation with automation and orchestration software solutions.
Our solutions scale to the needs of AI training cluster deployments in hyperscale facilities, to AI inference deployments in data centres and at the edge, ensuring any environment is ready for the demands of AI compute. No matter the size of your deployment, from traditional densities to extra high densities (200kW+), we have solutions to enable your deployment.
We provide end-to-end integrated solutions to support the global deployment and scale of your next-generation AI-ready data centres, from design to operations.
- Create a sustainable AI-ready data centre design.
- Secure AI-ready high-performance power trains.
- Implement hybrid and high-efficiency cooling solutions to run AI loads.
- Safeguard your operations with next-level proactive asset management services.
Take advantage of our top-notch products that ensure the smooth operation of data centres for AI use cases.
A data centre CFD software to help you optimise your data centres' cooling and energy consumption.
EcoStruxure IT Design CFD
Service Offer to digitise the customer's Single Line Diagram with ETAP software and provide ongoing model maintenance support in a recurring mode.
ETAP Digital Twin
Our consultants audit, evaluate, and map electrical and automation assets and systems, leveraging software to optimise and digitise those assets and systems.
EcoConsult
Next-generation service plan offering support from our experts enhance uptime, safety, and efficiency.
EcoCare
Our unique combination of sustainability leadership, sustainability consulting expertise, and data centre domain expertise means we can easily support you with a comprehensive environmental sustainability strategy, programme execution and reporting. Our goal is to help you decouple the growth of your AI data centres from their environmental impact.
Check how our five actions help ensure operational efficiency for data centres for AI.
Data Centre Sustainability
See how EcoStruxure Resource Advisor helps your business digitise ESG data and enhance ESG reporting.
EcoStruxure Resource AdvisorWe orchestrate a strong ecosystem of partners to effectively meet customer needs. By leveraging our extensive network of reliable channel ecosystem partners, we combine diverse expertise to create innovative solutions. They address a wide range of customer requirements across various industries and sectors.
Real Stories of challenge, success, and transformation that empower and showcase the impact of our solutions.
Compass Datacenters can ensure fast delivery and sustainability with their innovative supply chain.
Compass Data Centres
Blackstone achieves tens of millions in energy savings after introducing sustainability strategies and well-thought-out energy sourcing.
Blackstone
Animal Logic benefits from a high-performance computing prefabricated data centre that ensures maximum protection and effective data processing.
Animal Logic
Green Mountain is 100% powered by renewable energy and uses cold fjord water for cooling, leading to a 30% reduction in cooling costs.
Green Mountain
Leading Edge Data Centres aims to bring metropolitan-grade connectivity to regional Australia.
Leading Edge Data Centres
What is an AI data centre?
The AI data centre is a facility that stores a network of computing systems and infrastructure that support the high-demanding needs of artificial intelligence (AI) and machine learning applications. Their goal is to streamline information collection and then process it to generate efficient responses to user prompts entered by them.
The data centre for AI needs to have advanced hardware such as graphics processing units, field-programmable gate arrays, application-specific integrated circuits, and other equipment that optimise the processing and allow for complex computational tasks connected to AI operation.
What are AI data centre solutions?
Solutions that enable AI-ready data centres encompass numerous technologies, services, and strategies that optimise the infrastructure of data centres. The goal is to support both AI and machine learning workloads effectively. AI data centre design consists of hardware components in the form of AI-optimised servers and storage systems adapted to the specific operational conditions in which such systems work.
Additionally, AI-specific data centres require top-quality networking equipment and software solutions like AI frameworks, libraries, or even development tools that can ensure an efficient training, deployment, and then management of AI models.
How can our solutions help you develop your AI data centre?
Our solutions, specifically designed to accommodate the needs of inference and training workloads, help address the challenges and requirements of developing, upgrading, and maintaining AI data centres. With our expertise and technology offerings, your business can benefit from optimised hardware and software configurations specifically tuned for AI workloads and their needs.
Our services also include webinars that can broaden your knowledge of AI data centre solutions and show how to enhance your infrastructure and make it scalable, resilient, and energy efficient. Our expertise includes comprehensive support services, consultation, deployment, and ongoing AI data centre infrastructure management.
What are the key components of an AI data center?
An AI data center includes high-performance GPUs and CPUs for training models, scalable storage for massive datasets, and intelligent cooling systems for efficiency. It also features advanced networking, power management, and automation tools to ensure reliability, speed, and sustainability.
What role does networking play in AI data center?
Networking in an AI data center ensures high-speed data transfer between GPUs, servers, and storage. It reduces latency, supports massive data flows, and enables efficient AI model training and inference, ensuring scalability, reliability, and real-time collaboration across connected systems.
How is an AI data center different from a traditional data center?
An AI data center differs from a traditional one in its focus on high-performance computing for AI and ML workloads. It uses GPUs, low-latency networking, and advanced cooling to handle massive data processing, while traditional centers mainly support general IT and storage operations.
What challenges do businesses face in building AI data center?
Building an AI data center poses challenges such as high capital costs, complex power and cooling demands, and sourcing skilled talent. Managing massive data volumes, ensuring network efficiency, and maintaining sustainability while scaling infrastructure add to the operational complexity.
What role does networking play in AI data center?
Networking in an AI data center ensures seamless, high-speed data exchange between GPUs, servers, and storage. It supports massive data movement, minimizes latency, and enables efficient model training, real-time processing, and scalable AI performance across distributed computing environments.
Why is specialized hardware important in AI data center?
Specialized hardware like GPUs and TPUs is crucial in AI data centers to handle complex computations. It accelerates model training, reduces latency, improves energy efficiency, and supports large-scale data processing for advanced AI and machine learning applications.