Key takeaway: Data sovereignty and AI performance can be reconciled through hybrid infrastructures with GPU-as-a-Service and local data processing, but require elevated cybersecurity standards.
European enterprises must balance digital independence with efficient AI systems. An interview with the leadership of eww ITandTEL sheds light on how data sovereignty, GPU-as-a-Service, and new security requirements are reshaping data center architecture.
Enterprises in the DACH region increasingly face a conflict between data protection requirements and building powerful AI infrastructures. The expectation to keep sensitive data and computational capacity within their own sphere of responsibility cannot always be technically and economically realized in parallel with modern AI workloads that require specialized hardware such as GPUs.
According to Nermin Adzamija, Head of eww ITandTEL, infrastructure service providers must address this tension through hybrid models. This means: local data processing and secure control, combined with flexible, demand-driven resources for computational operations. GPU-as-a-Service offerings enable the provision of computational capacity without enterprises having to undertake expensive local hardware investments.
The increasing integration of AI into business processes directly drives new requirements for cybersecurity and data centers. Models that are trained or operated locally require isolated infrastructures with stronger network segmentation and differentiated access controls. At the same time, new attack surfaces emerge through the networking of AI systems with existing IT structures.
Source: itwelt.at · Published 24 June 2026
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