Find the practical solutions and insights to deliver fast, reliable, and scalable high-density infrastructure aligned with colos’ needs.
Enterprise leaders are investing heavily in artificial intelligence (AI). Management consulting firm Oliver Wyman’s 2025 survey of CEOs found that 95% view it as a business opportunity, with 83% of those executives actively deploying AI solutions. However, legacy infrastructure often can't meet AI's power and cooling requirements. While cloud solutions work for some use cases, applications requiring low latency, enhanced privacy, or strict security, demand on-premises or colocation deployment.
Delivering in the face of infrastructure challenges
AI workloads are fundamentally different from traditional computing:
- Higher power density: AI pods are projected to grow from 40-100 kW to over 100-250 kW in the coming years.
- Variable power demands: Unlike stable central processing unit (CPU) loads, graphic processing units (GPUs) exhibit rapidly fluctuating power usage patterns.
- Intense cooling requirements: High-density GPU clusters generate concentrated heat that strains conventional cooling systems.
- Fast scalability and deployment: Demand for high-performance computing (HPC) applications and services are increasing as more businesses consider employing AI for growth opportunities and efficiency.
- Changing skillsets and services: The fast changes in technologies are introducing new complexities, required skills, and technical knowledge gaps that inexperienced in-house personnel and vendors are only beginning to grapple with.
Colocation providers occupy a strategic position in the market, bridging the needs of enterprises for continuous reliability with infrastructure expansion capabilities. The growth opportunity is significant, and providers can lead the AI-enabled colocation market with infrastructure that delivers:
- Reliability: Adaptive power and cooling systems that maintain service level agreements (SLAs) while supporting denser, more variable loads.
- Efficiency: Advanced thermal management and power delivery that preserves the colocations’ cost and business advantage.
- Scalability: Modular solutions that grow with demand while managing resource consumption and efficiency.
Drawing on real-world implementations and emerging best practices, this white paper provides guidance and practical insights on:
- Adapting power systems for AI's unique requirements, including managing dynamic loads, implementing grid support capabilities, and optimizing power distribution for high-density racks
- Balancing air and liquid cooling strategies to efficiently remove heat from AI compute pods while maintaining flexibility across different density zones
- Leveraging reference designs and pre-configured solutions to accelerate deployment and reduce implementation risks
- Planning for scalable growth through modular infrastructure and strategic capacity management, including end-to-end services from experienced and collaborative partners.
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