Corporate and Government Competition Over AI Sovereignty Accelerates

The debate over AI usage is shifting from comparisons of performance and price toward the question of 'who controls AI.' A symbolic example of this shift is AI startup Anthropic's imposition of certain restrictions on the use of its models. These restrictions extend beyond simple terms of service and reflect a larger structural change surrounding access to and control over AI.

Behind this trend lies the emergence of a concept called 'AI sovereignty.' This refers to placing the operation, data, and decision-making processes of AI systems under the control of one's own country or organization, rather than depending on external corporations or nations. Just as the location of data and the nationality of companies handling its processing became issues in the age of the internet and cloud services, the 'control' over AI models themselves has now become a question of national security and competitiveness.

This movement is being driven by both national governments and large corporations. Governments are becoming concerned about dependence on models provided by foreign companies when utilizing AI in critical national infrastructure and administrative services. Meanwhile, large corporations are reassessing the risks of handing over their operational data to AI vendors and increasing their interest in 'private deployment'—keeping and operating models within their own organizations. Anthropic's model restrictions can be understood as one example of these underlying tensions coming to the surface.

Anthropic's actions are particularly noteworthy because the company is known as a pioneer in AI development that prioritizes safety. The company places AI risk mitigation at the center of its mission, and its model restrictions are an extension of that policy. However, the specific content and scope of these restrictions vary by company and use case, making it difficult to generalize.

This trend has the potential to impact the entire AI industry's business model. Traditionally, many AI companies have offered models widely through APIs and generated revenue through usage-based pricing. However, as customers increasingly demand 'control,' we can expect a shift toward business models that involve licensing models directly or enabling on-premises operation within companies' own facilities. For AI vendors, this presents new revenue opportunities while also creating the need to clarify technical support and liability boundaries.

The concept of AI sovereignty is both a technical question and a question at the intersection of politics, economics, and security. Questions about which countries can use which technologies and whose hands corporate data falls into are directly connected to future international AI governance discussions. Anthropic's case can be seen as merely the beginning of these discussions. Going forward, the terms of model access and alignment with region-specific regulations will be among the factors determining the competitive strength of AI companies.