Enterprises racing to put AI agents into production are discovering that role-based access control, not model choice, decides whether those agents can be trusted. Rising inference costs, privacy worries and sovereignty demands are also pulling more AI workloads back inside corporate data centers.

That shift favors companies that have spent years governing sensitive data at scale. Cloudera Inc. is betting on Cloudera Anywhere Cloud, a hybrid data and AI platform that spans public clouds and on-premises environments. The company has long been strong on governance, security and scalability but weaker on usability, a gap the new platform was built to close, according to Leo Brunnick (pictured), chief product officer of Cloudera.

“It turns out that the model is ultimately not going to be what separates your success from your competitor’s success,” Brunnick said. “The things that are going to separate you are, number one, your unique data. Your unique data and your unique processes, your alpha — what makes you a business.”

Brunnick spoke with theCUBE’s Rebecca Knight and Paul Gillin at EVOLVE26, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed why AI agents must follow users’ data permissions, the forces pushing AI workloads back into corporate data centers and how packaged blueprints and partnerships can simplify private AI adoption. (* Disclosure below.)