Overcoming AI Infrastructure’s Biggest Bottlenecks: Power, Cooling, and Data Center Design

Building the Resilient Infrastructure Needed to Support Next-Generation AI Workloads
AI adoption is accelerating faster than the infrastructure needed to support it. As data center energy consumption surges and grid connection delays stretch for years in key markets, organizations are facing mounting challenges around power availability, cooling efficiency, and facility design.
This ABI Research whitepaper explores the infrastructure strategies emerging to support the next generation of AI workloads. From microgrids and Small Modular Reactors (SMRs) to hybrid cooling architectures, digital twins, and standardized data center reference designs, the report examines the technologies and approaches helping operators build resilient, scalable AI infrastructure.
Topics Covered
- Power Availability Challenges: Why AI demand is outpacing grid readiness and creating infrastructure bottlenecks
- Alternative Energy Strategies: The growing role of microgrids, SMRs, battery storage, and distributed energy resources
- Cooling Innovation: How air cooling, liquid cooling, and hybrid approaches are evolving to support higher rack densities
- Reference Data Center Designs: Accelerating deployment timelines while reducing engineering complexity and risk
- Digital Twins: Using simulation and modeling to optimize capacity planning, cooling, and operational performance
- AI-Powered Operations: Building management platforms that improve efficiency, automate decision-making, and support uptime objectives
- Future Infrastructure Models: Exploring orbital data centers and other long-term approaches to overcoming infrastructure constraints
Download the whitepaper to learn how the industry is addressing the power, cooling, and design challenges that will shape the future of AI infrastructure.
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