---
id: "action-redesign-compute-location"
type: "action-item"
source_timestamps: ["§ The Incumbent's Energy Playbook", "¶14"]
tags: ["cloud-architecture", "location-strategy"]
related: ["concept-shiftable-vs-latency-sensitive", "prereq-cloud-architecture", "question-latency-vs-shiftable-threshold"]
speakers: ["Yinuo Tang", "Eric Yanfei Zhao"]
action: "Shift flexible AI workloads to cloud regions with cheaper, cooler, and less constrained power grids."
outcome: "Lowers energy costs and mitigates the risk of compute unavailability due to local grid constraints."
sources: ["futures"]
sourceVaultSlug: "hbr-seg-futures"
originDay: 2
articleStem: "hbr-nm-101-energy-strategy-ai"
sourceUrl: "https://hbr.org/2026/06/your-company-needs-an-energy-strategy-for-ais-next-phase"
sourceTitle: "Your Company Needs an Energy Strategy for AI’s Next Phase"
---
# Select cloud regions based on power availability

## Action
Shift flexible AI workloads to cloud regions with cheaper, cooler, and less constrained power grids.

## Detail
Transition to a **selective, multi-region cloud strategy** that weighs power availability, grid constraints, and cooling technology **alongside** traditional metrics like latency and compliance. Shift analytics and training workloads — the [[concept-shiftable-vs-latency-sensitive|shiftable]] category — to regions offering cheaper, cooler, and lower-carbon power (e.g., Nordic data centers). Requires the mental model in [[prereq-cloud-architecture]].

## Open dependency
Executing this cleanly depends on resolving [[question-latency-vs-shiftable-threshold]] — knowing which workloads truly must stay near users.

## Outcome
Lowers energy costs and mitigates the risk of compute unavailability due to local grid constraints — Step 4 of [[framework-incumbent-energy-playbook]].