ADI built a bottom‑up view of U.S. data center electricity demand driven by AI workloads, using rack density, GPU power consumption, utilization assumptions, and load growth scenarios. These demand estimates were stress‑tested through interviews with utilities, hyperscalers, and power developers to assess grid constraints and timing mismatches. The work linked physical load growth to regional power pricing outcomes over the next decade.
The client
Integrated energy company
The situation
Rapid AI growth created uncertainty around load growth, grid constraints, and power pricing.
ADI’s contributions
Proprietary demand modeling
Modeled load growth using bottom‑up GPU and rack‑density assumptions.
Primary market interviews
Interviewed utilities, data center operators, and OEMs.
Supply constraint analysis
Assessed transmission and grid bottlenecks by region.
Pricing outlook
Developed electricity price trajectories across scenarios.
Key outcomes
Established demand and price scenarios to support gas‑to‑power and infrastructure strategy.
Client Results
Working with ADI has been great for getting real customer feedback and targeting the specific information we are looking for.
ADI structured and led a workshop examining how AI‑driven data center growth translates into power demand, infrastructure strain, and planning risk. Insights were synthesized from utilities, hyperscalers, OEMs, and developers to assess demand magnitude, geographic concentration, and timing relative to transmission and permitting constraints. The analysis framed implications for fuel mix, grid investment sequencing, and […]
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