Gartner predicts that by 70, businesses will turn to local AI to control digital sovereignty.

Gartner predicts that by 2570, over 35% of countries worldwide will be restricted to using regionally specific AI platforms, indicating that a global model may not be suitable for current business models.

March 9, 2569 – Gartner Inc. A leading business and technology research and consulting firm revealed that: By 2570, over 35% of countries worldwide will be restricted to using region-specific AI platforms that rely on specific contextual data. Gartner also predicts that by next year, the level of monopoly on this platform will increase from 5% to 35%.

Gorav Gupta, Vice President of Analysis at Gartner. said "Countries aiming for digital sovereignty are increasing investment in domestic AI stacks to explore alternatives to the closed, US-based model."

This encompasses computing performance, data centers, infrastructure, and models that operate in accordance with their respective laws, cultures, and regions. Trust and cultural compatibility become key criteria, with decision-makers prioritizing AI platforms that align with local values, governance frameworks, and user expectations over platforms that simply possess the largest training datasets.

Localized models offer greater contextual value, with regional, large-scale language models (LLMs) outperforming global models in applications such as education, legal compliance, and public services, particularly in languages ​​other than English.

Many countries need to invest 1% of their GDP by 2572 to build AI sovereignty.

As clients outside the West begin to shift their stance due to concerns about excessive Western influence, AI sovereignty is becoming a key driver of reduced cooperation and redundancy. Consequently, Gartner predicts that countries building their own AI infrastructure, or sovereign AI stacks, will need to spend at least 1% of their GDP on AI infrastructure by 2572.

AI sovereignty refers to the ability of a country or organization to independently control the development, implementation, and use of AI within its geographical boundaries.

Regulatory pressures, geopolitical challenges, national cloud storage requirements, national AI missions, various risks facing organizations, and national security concerns are all driving governments and organizations to accelerate investment in sovereign AI. Furthermore, the fear of falling behind in the AI ​​technological competition is pushing countries and companies to innovate and invest towards achieving self-reliance across all aspects of their AI infrastructure.

"Data centers and AI factory infrastructure are the crucial backbone of the AI ​​stack, enabling AI sovereignty. This will lead to massive expansion and investment in these data centers and infrastructure in the future, driving the few companies that control this AI infrastructure to achieve double-digit, trillion-dollar valuations." Gupta added.

For all these reasons... Chief Information Officers (CIOs) must:

• Design workflows that are not tied to any particular model, using multiple management layers, enabling switching between LLMs in different regions and with different providers.
• AI is regulated and data is stored domestically, and model optimization adheres to the specific legal, cultural, and linguistic requirements of each country.
• Build relationships with national cloud providers, regional LLM providers, and leaders in sovereign AI in key markets, and compile a verified list of partners.
• Stay informed about new AI laws, data sovereignty regulations, and standards that may impact where and how AI models are deployed and user data is processed.

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