The Four Layers of Enterprise Sovereign AI
AI dependency does not exist in one place. It exists across the stack.
You can control where your AI runs and still be dependent on the model behind it. You can switch models while sensitive data remains outside your control. And you can manage both while being locked into applications and workflows that are difficult to change.
That is why enterprise Sovereign AI cannot be reduced to a single technology or deployment decision. It has to be considered across four connected layers: infrastructure, data, models and applications.
The objective is not to eliminate every external dependency. That would neither be practical nor necessary. The goal is to understand where dependencies exist, which ones matter most and where an organization needs greater control.
Infrastructure: Where Does AI Run?
Every AI capability ultimately depends on infrastructure.
This includes the compute environment running models and applications, the availability of processing capacity and the...
Copyright of this story solely belongs to hackernoon.com. To see the full text click HERE
