For enterprises and governments with strict compliance and sovereignty requirements, keeping sensitive data on-premises often means missing out on the latest AI. These organizations are managing three major risks:
- Jurisdictional risk: Shifting local regulations, the need to protect intellectual property and the potential of foreign data access requests make local data handling essential.
- Economic independence: Reliance on foreign infrastructure providers could leave critical services vulnerable.
- Geopolitical risk: A need to safeguard critical local services against unpredictable global disruptions.
In a recent survey of over 1,400 senior IT leaders for our State of AI Infrastructure report, 48% of leaders stated they are prioritizing infrastructure with data residency, controls, supporting compliance, with local data security laws.
However, staying on-premises no longer means being cut off from the latest innovation. Organizations are increasingly deploying hybrid (on-premises and multicloud solutions) to bridge this gap. Our research shows that 52% of organizations now have a hybrid cloud approach to AI.
This approach allows enterprises to balance the massive raw power of the public cloud with the sovereignty and compliance benefits of local environments — allowing them to control where their data resides and who has access to it. In the past, organizations with such strict data rules couldn’t easily access advanced AI. Building their own AI systems was also too slow and costly.
That is why we introduced Google Distributed Cloud (GDC). GDC brings Google Cloud to wherever you need it — in your own data center or at the edge. It is offered in two deployment models to meet your AI workload sovereignty requirements:
- Air-gapped: A fully disconnected solution that does not require connectivity to Google Cloud or the public internet. It cannot be remotely shut down by Google.
- Connected: An integrated, Google-managed software lifecycle that runs directly on your existing hardware.
GDC offers a complete, on-premises AI solution with infrastructure optimized for AI workloads, a choice of Gemini or open models, and cost-effective inference services. This foundation empowers you to build and run secure AI agents while maintaining total control over your data.
Meet your sovereign AI needs on-premises
You no longer have to choose between data control and AI innovation. With Google Distributed Cloud, we bring the world’s leading AI directly into your environment — keeping your data entirely yours.
Explore the hybrid strategies of leading enterprises in the State of AI infrastructure report.
By:Ankur Mehrotra (VP/GM, Distributed & Sovereign Cloud, Google Cloud)
Originally published at: Google Cloud Blog
