Gartner expects that by 2027, 35% of countries will be locked into region-specific artificial intelligence platforms built on proprietary contextual data, up from an estimated 5% today. The firm attributes the projected increase to growing geopolitical, regulatory, and security pressures that are prompting governments to invest in independent AI infrastructure aligned with domestic requirements.
According to Gartner, countries pursuing digital sovereignty objectives are allocating resources to develop domestic AI stacks that encompass computing capacity, data centres, infrastructure, and models designed to comply with local laws and cultural norms. Gaurav Gupta, a vice president analyst at the firm, said that trust and cultural compatibility are becoming central considerations for decision-makers, who are increasingly favouring platforms aligned with local regulatory frameworks and user expectations rather than those trained on the largest global datasets.
The firm notes that localised models can deliver higher contextual relevance, particularly in areas such as education, legal compliance, and public services, where regional language support and regulatory alignment are critical. In many non-English environments, regional large language models are assessed as outperforming global alternatives for these use cases.
Gartner also projects that countries seeking to establish sovereign AI capabilities will need to invest at least 1% of gross domestic product in AI infrastructure by 2029. The firm links this requirement to reduced international collaboration and duplicated development efforts as non-Western customers reassess reliance on AI technologies perceived to reflect Western priorities. In this context, AI sovereignty is defined as the ability of a nation or organisation to independently control the development, deployment, and use of AI within its geographic boundaries.
Regulatory demands, geopolitical considerations, cloud localisation requirements, national AI initiatives, corporate risk management, and national security concerns are cited as factors accelerating investment in sovereign AI. Gartner adds that concerns about lagging in technological development are encouraging governments and companies to pursue rapid innovation aimed at self-sufficiency across the AI stack.
Gupta said that data centres and AI factory infrastructure are becoming the foundation of these efforts, adding that increased construction and investment in such facilities are expected as countries seek greater control over AI capabilities. He noted that this trend could concentrate value among a limited number of companies that provide core AI infrastructure, though Gartner did not identify specific firms.
In response to these developments, Gartner advises chief information officers to adopt model-agnostic workflows that allow switching between AI models across regions and vendors, ensure governance and data residency practices meet local legal and cultural requirements, develop partnerships with national and regional AI providers, and closely track evolving AI legislation and data sovereignty standards that may affect deployment and data processing strategies.
