HSCALE: Fulfilling the Power Requirements of AI Clusters

2026-05-27 · Source: AI Magazine · Field: Technology & Digital — Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

HSCALE has secured 250MW of power capacity across two new hyperscale data center campuses in Northwest Milan, committing over US\$2.32bn (€2bn) to their delivery by 2028. These facilities are specifically designed to support high-density AI deployments alongside traditional cloud computing, featuring a flexible cooling infrastructure that allows operators to switch between air-cooled, direct liquid-cooled, and hybrid configurations without structural changes or additional capital expenditure. HSCALE emphasizes delivery certainty by fully owning both sites and having power already committed, addressing common project delays. Nearly 50% of the power supply will come from renewable sources, with plans to increase this share, utilizing a partnership with Aquila Clean Energy for integrated renewable energy. Milan is positioned as a strategic AI infrastructure location due to its connectivity and energy availability, offering an alternative to capacity-constrained Northern European markets. The project is backed by Bain Capital.

Key takeaway

For AI Architects or MLOps Engineers planning high-density AI infrastructure, you should prioritize data centers offering flexible, hybrid cooling solutions to accommodate evolving chip architectures and mixed workloads. Consider providers like HSCALE that secure committed power and integrate renewable sources, as this approach mitigates deployment delays and stabilizes energy costs. Your long-term capacity planning benefits from facilities designed to avoid bottlenecks and ensure delivery certainty in growing markets like Milan.

Key insights

HSCALE's Milan campuses offer flexible, high-density AI infrastructure with committed power and renewable energy, addressing critical operational challenges.

Principles

• Building design should not bottleneck evolving AI workloads.
• Flexible cooling infrastructure adapts to changing chip architectures.
• Site ownership and committed power ensure project delivery.

In practice

• Deploy hybrid cooling for mixed AI/cloud workloads.
• Prioritize sites with committed power and permitting.
• Integrate renewable energy for predictable power costs.

Topics

• AI Clusters
• Hyperscale Data Centers
• Data Center Cooling
• Renewable Energy
• Milan Infrastructure
• Infrastructure Investment

Best for: CTO, VP of Engineering/Data, Investor, AI Architect, MLOps Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.