AI is fundamentally changing the requirements for data centers. High power densities, increasing regulatory requirements, and the desire for greater control over data and infrastructure are forcing companies to make new strategic decisions. Learn why colocation for AI workloads should be reassessed and what requirements a sovereign IT infrastructure must meet.
Why AI workloads are increasingly turning infrastructure decisions into a strategic issue
What challenges arise from compliance requirements, cloud costs, and dependencies on hyperscalers
How colocation enables greater control over hardware, data location, and IT infrastructure
What technical requirements data centers must meet for high-performance AI and GPU workloads
What a sovereign, high-performance, and energy-efficient data center infrastructure can look like, using FRA7 as an example
The complete whitepaper
The 3 most important learning objectives (key benefits)
Strengthen digital sovereignty
Learn how companies can use colocation to retain control over hardware, data, and the software stack while benefiting from professionally operated data center infrastructure.
Future-proof planning for AI infrastructure
Learn what requirements AI workloads place on power density, cooling, connectivity, and availability—and what companies should look for when selecting a data center.
Better control compliance and costs
Understand how a clearly defined data location, transparent access rights, and predictable infrastructure models can help meet regulatory requirements and make long-term IT costs more predictable.