Discover how AI is transforming mission‑critical infrastructure: From modular data center design and liquid cooling to extreme power density to purpose‑built AI facilities, Steve Altizer, President and CEO of Compu Dynamics, covers these topics in this recent conversation.
At PTC 2026 in Hawaii, Isabel Paradis of HOT TELECOM held a discussion with Altizer to discuss how AI is reshaping the way modular data centers are designed now and in the future.
AI Is Rewriting the Rules of Data Center Design
AI is transforming data centers. While many are still trying to shoehorn AI workloads into traditional designs, that approach is only going to last a few more years. Hyperscalers are leading the way into an AI‑centric future, where liquid cooling – once a specialty – is now becoming standard across the industry.
Retrofitting conventional colo or cloud facilities for AI is not ideal. It’s not as cost effective as doing something that’s purpose built, yet building AI‑only facilities also carries risk, because repurposing that heavy investment later is difficult. The industry is therefore moving toward modular infrastructure, which allows for hybrid, purpose‑built AI facilities that remain flexible enough to serve a range of customers.
Engineering Infrastructure for AI‑First Data Centers
Compu Dynamics Modular (CDM) is tackling these demands. The company is focused almost exclusively on engineering infrastructure for AI and HPC data centers in order to meet tomorrow’s needs.
CDM’s compact IT spaces are roughly 600 square feet and can fit about 2.5 megawatts, roughly 4,000 watts per square foot versus the typical 300 watts per square foot seen in traditional builds. This shift proves that building data centers that are properly sized and optimized for the application inside is the most efficient way to tackle modern requirements.
Future‑Proofing Data Centers for AI Workloads
Looking ahead, AI will continue to explode across the sector. To future‑proof facilities, Compu Dynamics is embedding flexibility into designs, supporting varying rack densities and multiple profiles for inference versus training, including edge and centralized deployments.
Watch the full interview to dive deeper into designing AI-ready data centers and why enterprises need to rethink how their facilities evolve to keep pace with the AI era.
