Autonomous infrastructure breaks data silos to accelerate enterprise AI
Data intelligence is becoming the next battleground for enterprise AI and autonomous infrastructure as companies discover that copying information into dashboards and data lakes is too slow for agentic workloads. The shift is forcing IT teams to rethink architectures built for applications first and data second.
That debate is also reshaping how infrastructure companies frame their AI strategies, as recent SiliconANGLE coverage of Pure Storage shows. Breaking application silos and turning scattered repositories into live context for AI is now a core goal, according to Chadd Kenney (pictured), vice president of product management at Everpure Inc.
“If you were able to break down those silos, take the context and share it across each one of these applications and then later build a system of record with all of that data consolidated, AI agents now could actually be running on top of real-time data versus this latent copy,” Kenney said. “If they only have access to Salesforce data, they would have to infer what the costs are and maybe just make up what would be profitable or not. If they understood what suppliers were, what the costs were and also what the total product cost was, they could actually infer what a profitable order is and make that workflow work.”
