A third of countries are projected to adopt region-specific AI platforms within the next two years, according to new research from Gartner. This trend toward enhanced data sovereignty, driven by geopolitical tensions and regulatory pressures, comes at a significant cost to nations as they seek to bolster data protection frameworks, particularly in Europe.
The European Parliament recently mandated the European Commission to explore strategies for the EU to minimize its dependence on foreign AI providers. Current estimates indicate that EU member states rely on non-EU nations for over 80% of their digital products, services, and infrastructure, raising alarms among lawmakers about the implications for data security.
As enterprise AI adoption accelerates, Gartner forecasts a surge in the number of organizations utilizing regional platforms, expected to rise from 5% today to 35% by 2027. The urgency of this transition stems from a combination of factors, including regulatory requirements, cloud localization initiatives, corporate risks, and national security concerns, all of which are amplified by a fear of losing ground in the global AI landscape.
“Countries with digital sovereignty goals are increasing investment in domestic AI stacks as they look for alternatives to the closed US model,” said Gaurav Gupta, VP analyst at Gartner. He highlighted the importance of developing computing power, data centers, and infrastructure that align with local laws, cultures, and regional needs. Trust and cultural compatibility are becoming critical factors in AI platform selection, with decision-makers placing a higher priority on local alignment than on sheer data volume.
Sovereign AI efforts will be costly
However, Gartner warns that the shift towards sovereign AI will not come without significant expense. The drive for AI sovereignty is likely to result in reduced collaboration and increased duplication of efforts among nations. Consequently, Gartner estimates that countries pursuing a sovereign AI stack will need to invest at least 1% of their GDP on AI infrastructure by 2029.
Gurpta emphasized that data centers and AI factory infrastructure form the essential backbone of the AI stack necessary for achieving AI sovereignty. This anticipated demand is expected to propel select companies that control various aspects of the AI stack into double-digit, trillion-dollar valuations.
For IT leaders, the challenge of implementing sovereign AI projects presents a complex landscape. Gartner advises that Chief Information Officers (CIOs) must design platforms with sovereignty in mind. Compliance with country-specific legal, cultural, and linguistic requirements in areas such as AI governance and data residency will be crucial.
CIOs will also need to stay abreast of evolving AI legislation and data sovereignty regulations, which may dictate how AI models are deployed and how user data is processed. Establishing partnerships with national cloud providers, local large language model vendors, and leading sovereign AI stack companies in priority markets will be essential. Although the costs associated with these initiatives may present a hurdle, many organizations appear ready to accept the additional financial burden.
A recent survey of UK IT decision makers conducted by OVHcloud indicated a willingness among nearly two-thirds of respondents to pay between 11% and 30% more for sovereign technology products that meet regulatory and sovereignty requirements. Only 6.5% of respondents expressed reluctance to pay a premium for such solutions.
The push for sovereign AI represents a critical evolution in the technology landscape, reflecting a broader desire among nations to enhance control over their data and technology infrastructures. As the global AI race intensifies, the implications of these shifts will reverberate across industries, influencing both technological innovation and geopolitical dynamics.
