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Learn how colocation providers can respond to demand and rapidly transform their facilities to support AI compute demands through advanced power systems, liquid cooling, and modular infrastructure solutions.

Artificial intelligence (AI) workloads are fundamentally different from traditional computing loads: Modern graphics processing unit (GPU)-based AI systems can draw up to more than 250 kW per rack—far exceeding traditional rack densities. These systems also require specialized power delivery and cooling solutions to maintain optimal performance and reliability. As enterprise leaders accelerate AI adoption, colocation facilities must evolve to support the unique demands of AI infrastructure.

Power infrastructure adaptation

To support AI deployments, colocation providers must modernize their power infrastructure in several key areas:

  • Grid independence: With AI driving unprecedented power demands, facilities are deploying battery energy storage systems (BESS) to reduce grid dependence and manage peak loads. These systems work in conjunction with uninterruptible power supply (UPS) systems with advanced features to provide extended backup power and help stabilize energy delivery.
  • Advanced UPS systems: Modern UPS platforms are specifically engineered to handle the variable power loads characteristic of AI functions. These systems deliver stable power even during rapid load fluctuations while offering modular scaling capabilities to support growing power demands.
  • High-density power distribution: Traditional low-voltage power distribution becomes inefficient at AI-scale densities. Providers are increasingly adopting medium-voltage distribution systems and advanced busway solutions to deliver more power with greater efficiency and flexibility.

Cooling innovation for AI

The thermal management challenge of AI compute requires higher-density cooling capabilities for increased adaptability to expansion and energy efficiency. One option is a hybrid approach combining traditional air cooling with advanced liquid cooling solutions. Key considerations include:

  • Direct-to-chip liquid cooling for removing up to 70% to 80% of rack heat load
  • Rear-door heat exchangers (RDHx) for flexible high-density cooling
  • Strategic placement of coolant distribution units (CDUs)
  • Comprehensive leak detection systems
  • Integration of air and liquid cooling systems for optimal efficiency

Providers must carefully balance these solutions based on their specific facility requirements and customer needs. This often involves detailed computational fluid dynamics (CFD) modeling and careful infrastructure planning, and continuous collaboration with an experienced vendor from conceptualization to equipment maintenance and end of life.

Scaling with speed and efficiency

To capitalize on the AI opportunity, colocation providers need strategies for rapid deployment and scaling. Two key approaches are emerging:

  • Reference designs: Standardized, pre-validated infrastructure designs specifically engineered for AI workloads help reduce deployment complexity and risk. These designs cover various scenarios from retrofits to new builds, supporting densities from 10 kW to over 250 kW per rack.
  • Preconfigured solutions: Factory-integrated, modular infrastructure solutions can cut deployment times by up to 50% compared to traditional approaches. These solutions arrive onsite pre-tested and are ready for installation, enabling faster time-to-market (TTM) and more predictable outcomes.

The path forward

Colocation providers need to focus on three core elements to find consistency and success in modernizing their facilities:

  • Reliability: Facilitating high availability for mission-critical AI workloads
  • Efficiency: Maintaining cost-effective operations despite increased power and cooling demands
  • Scalability: Supporting rapid growth while managing infrastructure costs and complexity

The transition to AI-ready infrastructure represents a significant evolution for the colocation industry. Providers who act now to upgrade their facilities and develop AI-ready capabilities will be well-positioned to meet the needs of this rapidly expanding market while maintaining the reliability and efficiency their customers expect.

Position colocation data centers to capture the growing AI opportunity while maintaining profitable operations.

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