What happened
- Vertiv and Deloitte Center for Integrated Research announced a collaboration to help enterprises decide where to run artificial intelligence workloads. An infrastructure guide developed by Vertiv and STL Partners classifies workload needs and connects them to deployment models and reference designs.
- It considers cloud, colocation, on-premises facilities and edge options, along with physical requirements that can constrain operations.
Why it matters
- Moving from a test to a service used every day changes the discussion. Computing capacity is only one part: an organization also needs available power, suitable cooling, networks, space, operational continuity and a budget to maintain equipment. A decision made without those details can produce an architecture that is too expensive or unable to handle demand peaks.
- The document is a guide from market participants, not a technical standard or independent assessment. Vertiv sells power and cooling equipment; Deloitte and STL Partners contribute analysis and services. That experience may help structure questions, but recommendations should be checked against site measurements and quotes from multiple suppliers.
- For Chilean companies evaluating data centers or on-premises compute, grid connections, permits, water and network capacity also constrain design. Location and heat load affect costs and timelines, so operations and infrastructure teams should be involved from the pilot stage. Sizing should not simply copy a hyperscaler’s pattern: inference, training and document retrieval have different usage and latency profiles. Cost estimates should include electricity tariffs, backup power, maintenance and replacement cycles, since these costs continue after a pilot ends. The framework may help organize requirements before an investment is committed.
What’s next
- The companies released the guide on October 14.
- The announcement does not describe a certification, implementation schedule or savings figures attributable to the framework.
Bottom line
AI deployment begins with a physical question: where are the power, cooling and connectivity the model will need?
Sources
Written by Mamífero. Edited by Rodrigo Cornejo. This draft was assisted by AI and requires human editing before publication. See how we select and verify these notes.