Building AI Infrastructure That Moves Business Forward
The right infrastructure enables faster performance, smarter scale and better outcomes from AI investments.
Laying the Groundwork for AI That Performs
AI adoption is accelerating — but as respondents revealed in the 2025 CDW AI Report, many organizations are discovering that their infrastructure can’t keep up. Models demand faster compute, massive data throughput and cloud-ready environments that most legacy systems weren’t designed to handle.
Bottlenecks, cost overruns and inconsistent results are common when infrastructure falls short. To unlock AI’s full value, organizations need a solid foundation that’s built for performance, flexibility and future growth.
Here’s how to prepare an infrastructure for what’s next in AI.
Making Infrastructure the Launchpad
CDW’s research1 discovered that outdated systems can hold back even the most promising AI initiatives. Organizations need high-performance environments that support complex models, large datasets and continuous innovation.
Building for AI means more than raw speed. It means infrastructure that can handle real-time data flow, scale across hybrid environments and adapt as demands grow. With the right foundation in place, teams can move faster from pilot to production.
9 in 10 organizations struggle with where to start
35% say their infrastructure is not ready for AI workloads
47% lack full confidence in their AI planning and implementation
Supporting Growth with Confidence
Once AI starts delivering value, demand grows. What begins as a single model often inspires new use cases across teams, departments and workflows.
Organizations need infrastructure that keeps up without creating new risks or inefficiencies. That means embracing hybrid and multicloud flexibility, building cost-effective scalability and ensuring performance never comes at the expense of control.
of AI workloads run in a private cloud
use hybrid cloud for AI workloads
use public cloud for AI workloads
Strengthening the Core with Security and Governance
As AI scales, so do the risks. Infrastructure must support strong security, enforce data governance and ensure compliance across every layer — from model training to inference. Embedding these capabilities in your environment gives teams greater visibility, stronger controls and the confidence to innovate responsibly.
Key Priorities
Integrated identity and access controls
Compliance-ready infrastructure and auditing
Centralized observability and telemetry
Secure data pipelines for hybrid environments
Built-in governance to support ethical AI use
Design for Now and What’s Next
AI is evolving fast. Infrastructure that works today needs to be ready for tomorrow. That means building flexibility, resilience and scalability into every layer. From initial strategy through optimization, success depends on an environment that grows with your ambitions.
CDW brings together infrastructure strategy, technical expertise and long-term support to help businesses modernize with confidence.
“The transformation we’re seeing is not a point in time. We’re not going to make this transformation and then be done.”
Joe Markwith, Chief Strategist for Mastering Operational AI Transformation, CDW
Are you ready to build smarter infrastructure with AI outcomes that matter?
Source: 1 2025 CDW AI Report