Google is expanding its push into on-premises artificial intelligence (AI) through Google Distributed Cloud, targeting organisations with stringent data sovereignty and compliance requirements. The offering is designed for enterprises and governments that need to keep sensitive data within local environments while leveraging advanced AI systems. A recent Google survey of over 1,400 senior IT leaders indicated that 48% prioritise infrastructure with data residency controls to support local data security laws. The research also found that 52% of organisations now employ a hybrid cloud approach to AI, combining on-premises systems with multicloud environments. Google identified three primary risks influencing decisions: jurisdictional risk, economic independence, and geopolitical risk. The platform extends Google Cloud services into customer-controlled environments and is available in two distinct deployment models: an air-gapped version, which operates fully disconnected from Google Cloud and the public internet, and a connected version, which uses a Google-managed software lifecycle while running on a customer's existing hardware. The service provides an on-premises AI environment that includes infrastructure for AI workloads, access to Gemini models and other open models, and inference services. The announcement comes amidst increasing competition among cloud providers to address the growing concerns of regulated industries and public sector customers. Amazon Web Services (AWS) and Microsoft, among other suppliers, have made similar moves to meet demand from customers in sectors such as government, defence, healthcare, finance, and critical infrastructure.