How to build a sovereign AI stack
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Discussions about “AI sovereignty” generally focus on two things: investment and capabilities. Countries are encouraged to fund national champions that can develop frontier AI models, build compute clusters and assemble domestic data pipelines. But while these steps do matter, they cannot, by themselves, deliver true AI sovereignty. For that, a fully contestable and interoperable AI stack is essential.
An AI stack contains multiple interdependent layers. Energy infrastructure feeds compute clusters. Compute (processing power) enables the training and operation of foundation AI models. Foundation models are wrapped in orchestration layers and deployed through cloud platforms. Applications and agents sit on top. Each layer must be contestable (firms can enter and exit the market easily), which depends partly on interoperability (different tools, models and systems can exchange information).
