Decision Area 01 / 07
Compute, power, cooling, and systems working together at scale
Decision Area 02 / 07
Power availability, sequencing, and transition strategy
Decision Area 03 / 07
Building, electrical, cooling, and physical infrastructure architecture
Decision Area 04 / 07
Modular infrastructure, phased expansion, and additive change
Decision Area 05 / 07
Capital efficiency, utilization, lifecycle value, and optionality
Decision Area 06 / 07
Site readiness, deployment sequencing, and the path to operations
Decision Area 07 / 07
Market, utility, regional, and competitive signals shaping infrastructure decisions
The AI Infrastructure Forum scheduled for October 20, 2026, at the Georgia Tech Global Learning Center in Atlanta has been cancelled. The planned sessions will not take place.
You can continue exploring the underlying technical subjects through Blueflux Insights, the Topic Hubs, and the Technical Library.
Explore related guidance on energy storage and power strategy, conversion and distribution architecture, and digital twins for OT cyber defense.
Georgia Power is building three high-voltage transmission lines and two substations to serve a large data center customer south of Atlanta. When transmission moves onto the schedule, time to power becomes an infrastructure strategy question.
Your compute requirement and utility schedule no longer match. That does not automatically mean the project must wait for full grid capacity. The better question is whether an earlier operating state can create enough value to justify its cost, risk, and transition requirements.
AI infrastructure increasingly runs on different clocks: compute platforms may change during development, data center construction follows another cadence, and grid connections can take years. The strategic challenge is deciding what must be fixed now and what should remain adaptable.
Data center power alternatives should be evaluated as operating configurations, not as a technology list. This framework compares utility-led, onsite, renewable, storage, hybrid, and phased strategies.
AI infrastructure is not merely a building filled with servers. It is a coordinated system in which power, distribution, cooling, compute, communications, and cybersecurity must support one operating mission.
Compare energy storage architectures against response time, duration, safety, lifecycle cost, reliability, and integration requirements for AI-scale data centers.
AI infrastructure discussion often outruns engineering reality. The next conversation must focus on connected technical decisions shaping reliable, scalable deployment.
Good infrastructure decisions depend on a small set of facts that materially change the answer. The challenge is separating decision-changing information from data that merely adds detail.
AI infrastructure is built by specialists, but it operates as one system. The critical decisions sit at the interfaces between power, distribution, cooling, compute, communications and cybersecurity.
An OT alert does not choose the response. Define when to contain and when a separately isolated environment can support useful, bounded observation.
