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Making AI an Asset, Not an Expense
As AI moves from pilots to production, enterprises must decide when consumption pricing still fitsβand when AI infrastructure should be treated as a productive asset.
Provided byHPE
When customers talk about AI costs, the conversation usually starts with token prices and ends with access to the latest, most capable model in the cloud. Do they always need that level of capability? Not necessarily. But that is often where the conversation goes.
As AI moves from experimentation to production, model choice is only part of the equation. When demand becomes steady and business-critical, a consumption-only approach can turn AI spending into a variable monthly line item that is difficult to forecast as usage, workloads, and model requirements change.
