The biggest obstacle to enterprise AI isn\u2019t models, data science talent, or even infrastructure.\u00a0 It\u2019s operations.<\/p>\n
Across today\u2019s enterprises, hybrid complexity has outpaced IT\u2019s ability to manage it. Applications, workloads, runtimes, and infrastructure now span on\u2011premises environments, public clouds, edge locations, and air\u2011gapped sites. Each layer brings its own tools, vendors, and operational language. The result is friction everywhere and a widening gap between AI ambition and operational reality.<\/p>\n
Latha Vishnubhotla<\/a>, chief platform officer at Hewlett Packard Enterprise, tells The New Stack the challenges begin on Day 2.<\/p>\n \u201cPeople can bring things up and make them functional very quickly,\u201d says. \u201cBut where they spend most of their time is after the infrastructure becomes functional. Day 2 to Day N is where they spend a lot of time.\u201d<\/p>\n That\u2019s the problem enterprises are running into now. It\u2019s not getting infrastructure up and running, but keeping it running, optimized, and reliable as AI workloads move from pilot to production.<\/p>\n Read on to dive into not only the Day 2 problem, but to learn how HPE\u2019s GreenLake hybrid cloud management platform<\/a> has grown to respond to this enterprise complexity \u2014 including that cross-platform infusion of agentic AI.\u00a0<\/p>\n Day 2 is when the hybrid cloud breaks down<\/p>\n In hybrid environments, operations teams aren\u2019t managing a single stack. They\u2019re juggling multiple runtimes, from bare metal and VMs to containers and AI\u2011native platforms.\u00a0 Infrastructure across compute, storage, and networking often from different vendors. Workloads spread across data centers, public clouds, edge, and disconnected sites.\u00a0 Legacy systems that were never designed to work together<\/p>\n Each layer has its own management tools and telemetry. When something goes wrong, the symptom rarely appears in the same place as the root cause.<\/p>\n \u201cAll these different tiers are talking to each other, but it\u2019s not linear. You have to comb through and figure out where the issue actually is.\u201d<\/p>\n \u201cAll these different tiers are talking to each other, but it\u2019s not linear,\u201d Vishnubhotla says. \u201cYou have to comb through and figure out where the issue actually is.\u201d<\/p>\n Day Zero provisioning may be fast. Day 2 operations are where complexity compounds and teams burn time reacting rather than optimizing.<\/p>\n More AI is making the ops problem worse<\/p>\n AI not only raises the stakes but also delivers a solution.<\/p>\n Enterprises want to run more AI workloads, but data centers have finite capacity. Power, cooling, cost, and sustainability constraints are real. That\u2019s why FinOps and GreenOps have become inseparable from infrastructure operations.<\/p>\n \u201cWhen you want to run these workloads, you have to ask: what\u2019s not being used?\u201d Vishnubhotla says. \u201cWhy am I wasting here? Should I move something? Should I retire it?\u201d<\/p>\n This is where traditional, human\u2011driven ops models start to break. There\u2019s too much data, too many layers, and too many dependencies to reason about manually, especially at enterprise scale.<\/p>\n The ops platform as connective tissue<\/p>\n What enterprises need isn\u2019t another point tool. It\u2019s an operations platform that acts as connective tissue across the hybrid estate.<\/p>\n That\u2019s the role GreenLake is designed to play.<\/p>\n GreenLake provides a unified platform experience for running and managing hybrid environments across on\u2011premises, private cloud, edge, and collocated infrastructure while preserving choice and control. Instead of hiding infrastructure behind abstraction, it makes it visible, observable, and operable from a single control plane.<\/p>\n \u201cThe control plane is actually running in the cloud,\u201d Vishnubhotla says. \u201cYou get visibility across the entire estate.\u201d<\/p>\n For organizations managing thousands of sites and tens of thousands of devices, that visibility is foundational. But visibility alone isn\u2019t enough anymore.<\/p>\n Why agentic AI changes everything<\/p>\n The next step is agentic AI, AI systems embedded directly into the ops platform, trained on the context of specific infrastructure domains.<\/p>\n A networking agent understands networking. A storage agent understands storage. A compute agent understands compute. Each brings deep, domain\u2011specific intelligence to Day 2 operations.<\/p>\n \u201cEach layer already has intelligence,\u201d Vishnubhotla says. \u201cIf we can connect this intelligence, we can unleash very powerful outcomes.\u201d<\/p>\n