Vertiv Guides AI Deployment for Enterprises
News related to:Vertiv Holdings Co · 3 min read
COLUMBUS, Ohio, Oct. 14, 2026 /CourierPR/ -- New deployment guidelines, informed by Vertiv and STL Partners research, are helping organizations determine where to deploy their artificial intelligence workloads and whether the available physical infrastructure can support them. The new Vertiv Designing Infrastructure for Enterprise AI Guide, developed by Vertiv and STL Partners, provides business, IT, and facilities leaders with a framework for making those decisions before committing to an infrastructure plan. Starting with the intended business outcome and AI workload, organizations can evaluate deployment location, infrastructure requirements, and facility readiness, then align each workload with an appropriate physical infrastructure model and reference design for further planning and technical validation.
The research highlights a critical consideration as enterprises move AI workloads into sustained production: infrastructure readiness can determine where workloads can be deployed and how quickly they can move into production. Available power, cooling, connectivity, and operational capacity can determine whether a workload can be supported in an existing facility or requires a different deployment model.
The guide translates these considerations into a four-step process: defining the intended business outcome and AI workload, evaluating the workload's scale, performance, and operating requirements, determining the most appropriate deployment location, and matching the workload and location to a physical infrastructure model and reference design.
The process also recognizes that enterprise AI is a portfolio of workloads rather than a single infrastructure decision. Exploratory workloads may remain in the cloud, while sustained or business-critical workloads may favor hybrid infrastructure or capacity managed by the enterprise. Workloads requiring faster response times, greater control, data proximity, or specific model performance may need to run at the edge or in another controlled environment.
The guide categorizes enterprise AI workloads into six archetypes, covering model development, retraining, and four categories of production use. These archetypes help organizations identify workloads with similar performance, operating, and infrastructure requirements, creating a more consistent basis for planning. Each workload can then be aligned with one of four physical infrastructure models: Edge AI Cluster, Small AI Cluster, Large AI Cluster, and High-Density AI Cluster.
The four models provide a starting point for decisions involving power, cooling, controls, connectivity, resilience, operational support, and future growth. Corresponding reference designs can then be adapted based on site assessment, workload requirements, and detailed engineering.
Facility readiness is critical across all four models. The guide helps enterprises evaluate whether a proposed location has sufficient power, cooling, connectivity, operational capacity, and room for growth. Conducting this assessment early can help identify infrastructure constraints before they become barriers to deployment.
The full guide, Designing Infrastructure for Enterprise AI, details the six workload archetypes, four physical infrastructure models, and a four-phase roadmap for planning, deploying, and evolving enterprise AI infrastructure. It is available at www.vertiv.com/en-us/insights/industry/designing-infrastructure-for-enterprise-ai.
Vertiv Holdings Co. (NYSE: VRT) brings together hardware, software, analytics, and ongoing services to enable its customers' vital applications to run continuously, perform optimally, and grow with their business needs. Vertiv solves the most important challenges facing today's data centers, communication networks, and commercial and industrial facilities with a portfolio of power, cooling, and IT infrastructure solutions and services that extends from the cloud to the edge of the network. The company operates in more than 130 countries. For more information, and for the latest news and content from Vertiv, visit Vertiv.com.
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