Enterprises and governments face challenges in adopting AI due to strict data compliance and sovereignty requirements, often necessitating on-premises data storage. These organizations must manage jurisdictional, economic, and geopolitical risks associated with foreign data handling. A recent survey revealed that nearly half of IT leaders prioritize infrastructure supporting data residency and local security laws. Historically, maintaining data on-premises meant forfeiting access to the latest AI advancements. However, the adoption of hybrid cloud approaches, combining on-premises and multicloud solutions, is now bridging this gap. This hybrid strategy allows organizations to balance public cloud power with local sovereignty and compliance benefits. It enables control over data location and access, which was previously difficult for those with strict rules. Building in-house AI systems was also deemed too slow and expensive for such organizations. Google Distributed Cloud (GDC) offers a solution by bringing Google Cloud capabilities to on-premises or edge environments. GDC is available in air-gapped and connected deployment models to meet AI workload sovereignty needs. It provides a complete, on-premises AI solution with optimized infrastructure, model choices, and cost-effective inference services. This empowers organizations to build secure AI agents while retaining full data control.