According to a new United Nations (UN) report, countries that rely on foreign artificial intelligence (AI) models, cloud infrastructure and data pipelines may gain access to AI but risk losing control over its standards, safeguards and adaptability to local needs.
The report, published by the Independent International Scientific Panel on AI, established by the UN General Assembly last year as the world’s first global scientific body on AI, comes at a time when the US administration had imposed restrictions on access to advanced models. Although the restrictions were lifted recently, the initial move had prompted calls in India to accelerate its sovereign AI ambitions. The UN panel examines the emerging opportunities and risks posed by AI.
Underscoring that the AI divide is not just about access but about the capacity to influence AI development, the panel said countries increasingly need compute infrastructure, whether public or private, located within their borders to maintain autonomy, leverage and national security. It noted that a growing market for sovereign AI infrastructure has emerged, with major economies investing in domestic compute.
The panel added that the capacity to respond to AI risks is unevenly distributed across countries, with most nations, including many advanced economies, lacking the technical expertise needed to assess frontier AI models or participate meaningfully in their governance. Compute infrastructure, evaluation expertise and data, including for different languages, are concentrated where AI is built, leaving most member states dependent on systems they cannot build, inspect, audit or fully adapt to local needs.
The panel warned that countries without their own infrastructure or testing capabilities risk missing opportunities to co-develop key technologies, shape governance frameworks, influence global standards and retain talent.
To address these gaps, it called for greater investment in domestic AI infrastructure through public funding and policies that attract private capital, alongside talent retention programmes, regional AI residencies, joint PhD programmes, AI literacy in schools and systematic reskilling of public servants.
