AI anywhere: How AI models, AI optimized cloud infrastructure, and edge unlock new business cases

Summary: On-premises computing is not new, but extending AI enabled cloud infrastructure from the cloud to on-premises deployments is. According to Omdia research commissioned by Google Cloud, 38% of banking institutions plan to deploy AI to hundreds of on-premises locations. The rapid pace of AI and gen AI innovations unlock new opportunities to solve complex, costly, and resource intensive use cases such as information retrieval (conversational search), chatbots, and retrieval augmented generation (RAG). For industries (e.g. retail, manufacturing, financial services, healthcare and life sciences, and telecom), using real-time insights, enhancing customer experiences, and optimizing operations can make or break their competitiveness in the market. “AI anywhere,” a descriptive term for AI-optimized cloud infrastructure, AI models, and on-premises computing, is creating new opportunities for decision makers and developers alike to transform industry and public sector use cases including customer experiences, capitalize on new revenue opportunities, and boost business efficiencies. Challenge: Organizations today face a critical need to leverage AI across their operations, but several challenges hinder widespread adoption. Data gravity, stemming from regulatory requirements, cost concerns, and limited connectivity, often prevents moving data to the public cloud. Furthermore, latency-sensitive applications, such as real-time analytics, control systems, and user interfaces, demand processing power closer to the source, making traditional cloud deployments impractical. Modernizing legacy systems to integrate with AI presents additional complexities, while managing and securing AI deployments across multiple locations becomes increasingly burdensome as use cases expand. “AI anywhere” addresses these challenges by bringing the power of AI directly to where data resides and users operate, whether that's in the cloud, on-premise data centers, or at the edge. Solutions like