Vertiv Helps Enterprises Move from AI Pilots to Production
PR Newswire•14/10/2026•08:30 ET
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Key Highlights
- ➤Vertiv and Deloitte introduced an enterprise AI infrastructure planning collaboration
- ➤New guide maps AI workloads to deployment locations and infrastructure requirements
- ➤Research identifies six enterprise AI workload archetypes for production planning
- ➤Framework defines four physical infrastructure models: edge, small, large and high-density clusters
- ➤Guide evaluates power, cooling, connectivity and operational capacity before deployment
Expert Statements
Giordano Albertazzi, CEO of Vertiv
“The next phase of enterprise AI will be shaped not only by models and computing, but also by whether organizations can provide the power, cooling, connectivity and operating environment each workload requires”
Giordano Albertazzi, CEO of Vertiv
“By starting with the workload, enterprises can make infrastructure decisions earlier, identify constraints sooner and build a more credible path from AI ambition to production”
Nicholas Merizzi, principal, Silicon2Service U.S. Lead, Deloitte Consulting LLP
“The economics and operating requirements of AI change as workloads move into production”
Nicholas Merizzi, principal, Silicon2Service U.S. Lead, Deloitte Consulting LLP
“Organizations need to consider business value, governance, operating ownership and infrastructure together”
Nicholas Merizzi, principal, Silicon2Service U.S. Lead, Deloitte Consulting LLP
“Bringing those questions into the planning process earlier gives leaders a stronger basis for deciding where AI workloads should run and how they should be supported over time”
Vertiv Helps Enterprises Move from AI Pilots to Production PR Newswire
New deployment guide, informed by Vertiv and STL Partners research, helps organizations determine their AI archetypes and where the supporting infrastructure should be located
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