6 steps to weigh compromise and priorities for AI sovereignty

AI sovereignty is less about owning every layer of the AI stack and more about making deliberate trade-offs between speed, cost, flexibility, and control. The article argues that CIOs should design for portability, decouple applications from models, protect data and intellectual property, and avoid contracts or architectures that create long-term vendor lock-in as AI capabilities and pricing evolve rapidly. For IT organizations, this means building an adaptable foundation now—using open standards, modular tooling, and internal engineering skills—so the enterprise can switch models and providers without disrupting business operations.