The AI revolution is reshaping the digital infrastructure landscape, and data centers are at the heart of this transformation. Amazon’s recent $10 billion investment in North Carolina for new data center campuses is just the latest signal of how quickly this sector is scaling to meet AI’s demands¹. As an infrastructure executive, understanding and anticipating these shifts is essential.
AI workloads—especially large language models and generative AI—require enormous computing power, high-density GPUs, and ultra-low latency networks. This explosive demand is expected to drive a 33% annual growth in AI-ready data center capacity through the decade². Hyperscalers like Amazon, Microsoft, and Google are leading the way, but the ripple effects are felt across every enterprise-scale operation.
Power and Cooling Constraints
The power requirements for AI are immense, with some data centers now consuming electricity at the scale of small countries. Cooling these high-performance environments is an escalating challenge that traditional air-cooled systems can’t handle efficiently³.
Location, Scalability, and Latency
Core data center markets are increasingly saturated. Forward-looking operators are now turning to secondary and tertiary markets, which offer favorable permitting environments, lower energy costs, and proximity to edge users⁴.
Supply Chain Strain and Talent Gaps
From high-performance GPUs to construction materials and skilled labor, supply chains are stretched thin. CIOs must now forecast further out and establish partnerships to secure capacity and avoid project delays.
Diversify Power Sources
Incorporate renewable energy strategies and partner with utility providers for green power procurement.
Explore Modular and Edge Deployments
Modular builds and edge data centers offer flexible, rapid deployment and bring compute closer to where data is generated.
Leverage Colocation Marketplaces
Use platforms like colocapacity.com to identify and reserve available colocation space that aligns with your power and location requirements—especially in emerging markets.
Invest in Liquid Cooling
As densities rise, direct-to-chip and immersion cooling are becoming essential, not optional.
Design for Sustainability
Achieve long-term operational savings and environmental goals by designing around energy-efficient architectures and pursuing green certifications.
The infrastructure demands of AI are moving faster than many organizations are prepared for. Leaders who act now—investing in flexible power models, adopting advanced cooling, and leveraging smart colocation strategies—will be in the best position to capitalize on the AI boom. The question isn’t if AI will reshape your infrastructure. It’s how quickly you can adapt.
CNBC – Amazon to invest $10 billion in data centers to support AI boom (June 4, 2025): Link
McKinsey & Company – AI power: Expanding data center capacity to meet growing demand
Wikipedia – Environmental impact of artificial intelligence
DataCenterDynamics – The capacity crunch: Addressing spiraling data center demand
Colocapacity – Colocation marketplace for power-available facilities: colocapacity.com