Agentic AI: Ops Platform Key to Enterprise AI Success

The biggest obstacle to enterprise AI is operations, not models or talent. Hybrid complexity now outpaces IT's ability to manage it. Applications and infrastructure span various environments, each with its own tools and vendors. This creates significant friction. Latha Vishnubhotla, chief platform officer at Hewlett Packard Enterprise, highlights that challenges begin on "Day 2" after infrastructure is functional. Keeping systems running, optimized, and reliable for AI workloads moving from pilot to production is the problem. In hybrid environments, operations teams manage multiple runtimes and infrastructure from different vendors across various locations. Each layer has its own management tools. Vishnubhotla explains that different tiers talk to each other non-linearly, making it hard to find root causes when issues arise. More AI workloads exacerbate this operational problem, as data centers have finite capacity and constraints like power and cost. This is where traditional, human-driven operations models start to break down. This matters because efficient operations are crucial for integrating AI effectively into enterprise systems.