{"id":99923,"date":"2026-02-18T08:00:34","date_gmt":"2026-02-18T11:00:34","guid":{"rendered":"https:\/\/abes.org.br\/?p=99923"},"modified":"2026-02-03T12:00:57","modified_gmt":"2026-02-03T15:00:57","slug":"gartner-preve-que-35-dos-paises-estarao-presos-a-plataformas-de-ia-especificas-para-a-regiao-ate-2027","status":"publish","type":"post","link":"https:\/\/abes.org.br\/en\/gartner-preve-que-35-dos-paises-estarao-presos-a-plataformas-de-ia-especificas-para-a-regiao-ate-2027\/","title":{"rendered":"Gartner predicts that 351% of countries will be locked into region-specific AI platforms by 2027."},"content":{"rendered":"

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Geopolitical, regulatory, and security pressures are driving governments to increase investments in AI-independent infrastructure.<\/em><\/p>\n

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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.<\/span><\/p>\n<\/div>\n

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\u201cCountries 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,\u201d says Gaurav Gupta, Vice President Analyst at Gartner. \u201cTrust 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.\u201d<\/p>\n<\/div>\n

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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.<\/p>\n<\/div>\n

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Countries will need to invest 1% of Gross Domestic Product (GDP) in AI sovereignty by 2029.<\/b><\/p>\n<\/div>\n

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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.<\/p>\n<\/div>\n

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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.<\/p>\n<\/div>\n

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Regulatory pressures, geopolitics, location of\u00a0A cloud<\/a><\/u>, 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\u00a0AI technology race<\/a><\/u> 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. \u201cData centers and AI factory infrastructure form the critical backbone of the AI stack that enables AI sovereignty,\u201d says Gupta. \u201cAs 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.\u201d<\/p>\n<\/div>\n

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Therefore, Chief Information Officers (CIOs) should:<\/p>\n<\/div>\n