"Hyperscalers are making a strategic mistake by assuming AI buyers will accept traditional pricing strategies. AI buyers are training and deploying models, demanding more value for their investment."
"The issue is not that AWS, Microsoft Azure, and Google Cloud are expensive in absolute terms, but that they are becoming expensive relative to an expanding set of credible alternatives."
"Buyers will resist paying much more for little or no proportional benefit. In AI, it is increasingly difficult for hyperscalers to prove that their services offer higher model accuracy or strategic advantages."
Hyperscalers have relied on a straightforward value proposition, but AI is exposing flaws in traditional cloud pricing. As compute can be sourced cheaper elsewhere, the surrounding ecosystem must provide exceptional value to justify costs. AI buyers are not merely migrating applications; they are actively training and deploying models, leading to increased scrutiny from stakeholders. The real issue lies in hyperscalers becoming expensive relative to credible alternatives, making it crucial for them to demonstrate proportional benefits to justify their pricing.
Read at InfoWorld
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