Geopolitical, regulatory, and security pressures are driving governments to increase investments in AI-independent infrastructure.
By 2027, 351% of countries will be locked into region-specific Artificial Intelligence (AI) platforms using proprietary contextual data, according to Gartner, Inc., a technology and business insights firm. Gartner also predicts that platform reliance will increase from 51% to 35% by 2027.
“Countries with digital sovereignty goals are expanding investments in national AI stacks as they seek alternatives to the closed U.S. model, including computing power, data centers, infrastructure, and models aligned with local laws, culture, and region,” says Gaurav Gupta, Vice President 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, rather than those with the largest training datasets.”
Localized models deliver greater contextual value; regional Large Language Models (LLMs) outperform global models in applications such as education, legal compliance, and public services, especially in languages other than English.
Countries will need to invest 1% of Gross Domestic Product (GDP) in AI sovereignty by 2029.
With non-Western clients shifting their alignments due to concerns about excessive Western influence, AI sovereignty will lead to reduced collaboration and duplication of effort. For this reason, Gartner predicts that countries 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 Artificial Intelligence is developed, implemented, and used in relation to its geographic borders.
Regulatory pressures, geopolitics, location of A cloud, National AI missions, corporate risks, and national security concerns are driving governments and companies to accelerate investments in sovereign AI. The fear of falling behind in AI technology race It will also drive countries 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,” says Gupta. “As a result, data centers and AI factory infrastructure will see explosive expansion and investment volume, driving some companies that control the AI stack to double-digit valuations in the trillions of dollars.”
Therefore, Chief Information Officers (CIOs) should:
- Design model-agnostic workflows using orchestration layers that allow switching between LLMs in different regions and vendors.
- To ensure that AI governance practices, data residency, and model tuning meet the specific legal, cultural, and linguistic requirements of each country.
- Establish relationships with national cloud providers, regional LLM vendors, and leaders of sovereign AI stacks in priority markets, creating a validated list of partners.
- Monitor AI legislation, data sovereignty rules, and emerging standards that may affect where and how AI models can be implemented and user data processed.
Topics such as this and others related to data and Artificial Intelligence, including AI agents, governance, leadership, data science, and data architecture, will be highlighted during the event. Gartner Data & Analytics Conference, which will take place on April 28 and 29 in São Paulo (SP).
Gartner clients can learn more at “Predicts 2026: AI Sovereignty.”
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