The artificial intelligence moment has a new focal point, and it isn’t a model — it’s the mess of files, logs and transactions where work actually happens. The winners may very well be those who reshape that sprawl into a data-first architecture that moves operations close to where structured data lives.
As AI takes hold in workflows, enterprises are rethinking how they run for speed and reliability. Critically, efficiency follows the data and not vice versa, according to George Kurian (pictured), chief executive officer of NetApp Inc.
NetApp’s George Kurian talks with theCUBE about data-first architecture in the AI era.
“One of the things that we’ve observed is data has consistently grown in volume,” he said. “Taking actions at the point that the data is created is far more efficient than trying to copy the data into other places, transform it and then rewrite it back.”
Kurian spoke with theCUBE’s Christophe Bertrand at the NetApp Insight 2025 event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed why a data-first architecture matters in the age of AI workflows. (* Disclosure below.)
Data-first architecture at the source
NetApp — which today announced its AI Data Engine — suggests that getting value from data starts with basics, keeping compute at the source and avoiding redundant copies that widen attack surfaces and costs. With that said, agents are useful only when they run on curated data with defined semantics and access controls, where they can act as practical proxies for employees, Kurian explained.
“An agent eventually becomes a digital twin of an employee,” he said. “Every human will have some form of agent that operates on their behalf. For agents to work properly, you need a few things in the infrastructure. The first is to have high quality curated data on which the agents are operating so they don’t end up with a situation related to drift or poisoning of their results. The second is they need to be able to have guardrails.”
The hard line is then drawn, replacing app-first plans in favor of data-first architecture. Build the corpus, generate metadata and transform in place — then let application teams plug in, according to Kurian. That sequence, he argues, cuts waste and speeds collaboration with the people who ship software.
“We think that starting from the data out, as opposed to coming at it top-down, makes the processing efficient,” he said. “It allows us to collaborate with people building application stacks and really build the data for the workflows that will support these applications.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the NetApp Insight 2025 event:
(* Disclosure: TheCUBE is a paid media partner for the NetApp Insight event. Neither NetApp, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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