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Preparing for the vital but complex era of AI
Scott Sinclair · 2026-05-26 · via WhatIs

AI is becoming essential, but its complexity pushes businesses to modernize legacy systems, consolidate platforms and expand AI-driven automation.

During the opening keynote at this month's Red Hat Summit, Red Hat President and CEO Matt Hicks said, "The new-initiative pressure, the organizational friction, the legacy constraints all happening at once … that combination is the villain in the room."

Nearly every business leader accepts that success in AI is vital to the survival of their business. According to our Omdia research, 84% of organizations agree that AI is critical to their organization's future strategy.

But AI isn't easy. It's not another workload that can simply be deployed in the corner. It requires serious investment in budget and personnel, and the necessary investments will be more difficult to come by if your organization is already drowning in legacy infrastructure and technical debt. 

In addition, success in AI requires more than just the right infrastructure, data and tools. It requires top-down backing from executive leaders who have a fundamental understanding of how AI will transform a business's most important processes.

Hicks went on to address those business leaders and executives, saying, "[AI agents] will pressure test every process you have. And they will pressure test your ability to understand the technology, truly understand your processes, decompose complicated work and delegate to agents and to humans."

Combined, these two quotes exemplify Red Hat's vision for AI success. AI is vital but complex, and it will therefore require not only significant budget but also significant focus from IT admins, leaders and chief executives alike. And to best prepare for their businesses' futures as defined by AI, IT leaders should modernize as much of their existing legacy environment as possible.

They should concentrate on consolidating to a single platform that can support legacy -- think VMs in this case -- as well as more modern container-based applications and AI-enabled applications and agents. The idea is to simplify through consolidation and enable admins, developers, leaders and executives to focus the vast majority of their attention on solving the challenge of AI.

Tactical takeaways for IT from Red Hat Summit

For IT executives, the takeaway is that long-term AI isn't a side project or a silo. AI will be a fundamental aspect of multiple, if not all, areas of your business. With this in mind, IT organizations should look to modernize their legacy VM environments to establish a platform that supports mixed clusters of VMs and container-based workloads, while providing a path forward to support AI applications and agents and adopt AI-enabled tools for IT operations.

They should also focus on increased automation using AI-enabled tools to further reduce the burden on IT personnel from both legacy and modern operations.

Modernize and consolidate application environments for AI

To enable this modernization and consolidation vision, Red Hat OpenShift is designed to help enterprises modernize their environments to prepare for AI. Then, with Red Hat AI, Red Hat offers a portfolio of tools to help build, train and deploy AI models and agents on OpenShift infrastructure.

The challenge for many organizations, however, is the shift in experience and the jump in complexity that occur when moving from a VM-only environment to one that embraces containers. To assist with the first part, Red Hat introduced its OpenShift Virtualization Engine last year, providing a VM-only, upgradable flavor of OpenShift designed to ease adoption while offering a VM-only hypervisor alternative for organizations looking to make a shift in the near term.

This desire to optimize operations by comanaging VMs and containers on the same platform is increasingly being embraced by enterprises, thanks in part to rising hypervisor license costs. According to our research, 39% of organizations that experienced an increase in the price of their existing hypervisor environment identified plans to accelerate application modernization initiatives to shift more applications from virtual machines to containers. Another 39% identified plans to shift to a new platform that can support both VMs and containers.

Red Hat isn't alone in innovating to deliver a consistent platform to span VMs, containers and AI. For example, VMware recently increased the scale of its VMware vSphere Kubernetes Service in VMware Cloud Foundation 9.1. Nutanix recently announced bare-metal support for containers with Nutanix Kubernetes Platform Metal. And a few weeks ago, VergeIO announced Kubernetes support.

The overall complexity of container environments has often led enterprises to deploy container platforms, such as Kubernetes or OpenShift, inside VMs. In the long term, though, achieving optimal efficiency in both cost and performance for a combined VM, container and AI environment will likely require bare-metal container support.

Although Red Hat and others continue to innovate to simplify bare-metal container environments, more work remains to be done. And until this area of complexity is addressed more sufficiently, consolidation onto a single platform will likely still provide benefits in terms of functionality. Benefits to simplicity or freeing up admin time, though, might be harder to realize. 

Embrace AI-enabled automation and operational tools

The integration of AI into IT operations, IT service management, observability and automation platforms is already delivering substantial benefits. According to Omdia research, 39% of IT admins said that at least 50% of their tasks are handled in part by AI models or copilots.

At Red Hat Summit, I saw a demonstration of Ansible Automation Platform featuring several enhancements, including these updates:

  • The integration of context-aware AI.
  • An intelligent assistant that can use organization-specific data.
  • A Model Context Protocol server to connect other AI tools.
  • The automation orchestrator, which provides a visual flow-chart-like interface to build out logical workflows that use organization-specific data.

In addition, to simplify interoperability with other platforms, Red Hat offers guidance on integrating with partners such as IBM Instana, ServiceNow and Splunk.

With the combined use of AI and existing automation playbooks, the idea is to use the AI technology for introspection to understand the environment, identify potential issues and then use trusted playbooks to execute the operation, reducing the risk of hallucinations impacting the implementation of any changes or updates.

Looking ahead, we're entering the era of enterprise AI, where both the use of AI-enabled applications and agents is poised to expand rapidly. Waiting for AI to get easier isn't an option, given how quickly the pace is likely to move both internally and among your competition. AI is complex, so you need to ensure your business allocates sufficient budget and human resources to succeed. This requires freeing up resources elsewhere by optimizing legacy environments through modernization and consolidation and ramping up the use of internal IT-related AI and automation.

Scott Sinclair is practice director with Omdia, covering the storage industry.

Omdia is a division of Informa TechTarget. Its analysts have business relationships with technology vendors.

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