From the Deal Room
Buyers have professionalised. CUDO's primary research is a Censuswide survey of 701 infrastructure decision-makers across the UK, US and Europe (fielded February 12–25, 2026), complemented by a small qualitative interview programme. Survey findings are reported below with their base and question; interview and external material are labelled separately.
The winning pitch leads with token-level economics, power-secured timelines, goodput-based SLAs and sovereign-compliant architecture — not GPU counts.
What's actually constraining scale
Base: all 701 respondents. Constraint question is multi-select; cost-driver split is share of cost-driver selections. Figures are CUDO survey findings.
Top scaling constraints
Multi-select · % of 701 respondents selecting each barrier
Cost-driver split
71% of cost-driver selections are infrastructure
Hyperscaler capex supercycle
$B · $250B (2024) to $600B (2026)
Capacity-planning confidence by region
The market committing the most capital (US) reports the weakest grasp — 90.7% confident overall, from 98% in the UK to 82.6% in the US. Base: all 701 respondents.
Confidence in capacity planning
Single-select · % of 701 respondents
Credible sites vs. risky locations
✓ Credible signals
Pacific NW hydro
Lowest documented power cost (~$50,800/mo per 1,000-GPU cluster)
Nordic hydropower
Stargate Norway (Narvik) — abundant low-cost hydro, cool climate
Brownfield / industrial reuse
Jay, Maine; Hamilton “Steelport” — mitigates grid/environmental concerns
EU secondary markets
Berlin, Milan, Madrid, Warsaw, Nordics — decentralized away from scarcity
⚠ Risky signals
FLAP-D primary hubs
Grid-constrained; Ireland already at 22% of national electricity
Moratorium-exposed
Maine, New York, Hamilton (Ontario) — 75 projects (~$130B) disrupted
High power-cost markets
Japan / Germany >$300,000/mo per 1,000-GPU cluster
Single foreign-provider dependency
CLOUD Act reach & “sovereign lock-in” exposure
What buyers are really asking
Turn these signals into a placement decision
Discuss power, location, cluster architecture and TCO with a CUDO AI infrastructure specialist.
