Enterprise ambitions for artificial intelligence are outpacing the infrastructure and budgets needed to support them. Red Hat AI faces a familiar enterprise challenge: turning ambitious plans for artificial intelligence into production deployments that deliver measurable returns. Organizations must also decide how to deploy and manage increasingly complex AI workloads across existing infrastructure without letting costs spiral. At Red Hat Summit 2026 in May, Red Hat Inc. outlined its approach to those challenges through expanded platform capabilities, automation and an open-source development process that relies on community contributions. “I think everybody here loves that because that does lead to sovereignty as well,” said Rob Strechay, principal analyst at theCUBE, during the event. “They’re actually building on top of open source and enhancing it in a way that provides more value in supporting it, which is key to their success.” This feature is part of SiliconANGLE Media’s ongoing coverage of the AWS Financial Services Symposium. (* Disclosure below.) Red Hat expands support for AI across hybrid cloud environments Deploying and managing AI workloads across hybrid cloud environments presents new operational challenges for enterprises. Red Hat’s answer is Red Hat AI 3.4, an updated version of its enterprise AI platform that supports agentic...