One-Third of Countries Will Be Locked Into Region-Specific AI Platforms by 2027

By 2027, 35% of countries will be locked into region-specific AI platforms using proprietary contextual data, according to Gartner. The business and technology insights company also predicts that platform lock-in will rise from 5% to 35% by 2027.

“Countries with digital sovereignty goals are increasing investment in domestic AI stacks as they look for alternatives to the closed U.S. model, including computing power, data centers, infrastructure, and models aligned with local laws, culture, and region,” said Gaurav Gupta, VP Analyst at Gartner. “Trust and cultural fit are emerging as key criteria. Decision makers are prioritizing AI platforms that align with local values, regulatory frameworks, and user expectations over those with the largest training datasets.”

Localized models deliver more contextual value; regional LLMs outperform global models in applications such as education, legal compliance, and public services, especially in non-English languages. With non-Western customers changing alignment due to concerns of overly Western influence, AI sovereignty will lead to reduced collaboration and duplication of effort. Because of this, Gartner predicts that nations establishing a sovereign AI stack will need to spend at least 1% of their GDP on AI infrastructure by 2029.

AI sovereignty refers to the ability of a nation or organization to independently control how AI is developed, deployed, and used within its geographical boundaries. Regulatory pressure, geopolitics, cloud localization, national AI missions, corporate risks, and national security concerns are driving governments and corporations to accelerate investments in sovereign AI. A fear of falling behind in the technological AI race will also push nations and companies to innovate rapidly and invest in an attempt to achieve self-sufficiency in all aspects of the AI stack.

“Data centers and AI factory infrastructure form the critical backbone of the AI stack that enables AI sovereignty, " said Gupta. “As a result, data centers and AI factory infrastructure will see explosive build-up and investment going forward, propelling a few companies that control the AI stack to achieve double-digit, trillion-dollar valuations.”