Seven registers · one method Under development
An independent research organization assessing how governments, regions, cities, public institutions, corporations, industries and universities build, deploy and govern artificial intelligence — each on the same published method and the same 0–100 scale.
NA National governments 195 governments assessed
NA · National governments · 11 August 2026 Full register →
Global AI Rankings is under development. Scores are synthesized from publicly available data and presented as aggregated estimates produced by a stated method. They are not audited findings, certifications, ratings or statements of fact about any government, institution, company or individual, and they are subject to revision without notice.
The register Under development
A city and a corporation are not comparable to one another. Each is comparable within its own register, and the method that produced both is identical and published.
Overview Under development
Published strategy is now near-universal among assessed governments and no longer distinguishes between them. The Global AI Rankings therefore score what a state has established: institutions, compute and data infrastructure, workforce capability, and enforceable safeguards. Capability and control are weighted equally.
Since the first edition in 2025, the Global AI Rankings have addressed a single question: what does a government require to deploy artificial intelligence effectively and accountably, and how far has each one progressed? The scope is deliberately narrow. National AI industries, frontier model capability and private-sector adoption are assessed only where the state’s own capacity depends on them.
Policy capacity is now close to universal: 91% of assessed governments record a policy-capacity score above zero. Substantially fewer have established the machinery that converts a stated position into a governed deployment — a named accountable owner, a recurring budget line, a procurement route capable of acquiring AI systems safely, or a redress mechanism for individuals affected by automated decisions. The Rankings measure the distance between those two positions.
The 2026 edition covers 195 governments, built on the 69 indicators the source framework assesses across 14 dimensions. Where a government has not supplied evidence, the indicator is recorded as absent rather than estimated, and the omission is disclosed. Published gaps are preferred to inferred values.
Indicator-level data is published concurrently with the report. Governments, organizations and researchers may dispute a score through the corrections process. Every accepted correction is logged publicly with its date and its effect on the published result.
Explore the registers Under development
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Public-source synthesis
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Global AI Rankings synthesis methodology. Scores are synthesized from publicly available data, normalized to a common 0–100 scale and aggregated as estimates across six equally weighted pillars. The national register is current as of . The other six registers carry illustrative figures and must not be cited. Derivation and indicator weights are set out in the methodology.
Global AI Rankings is under development. Scores are synthesized from publicly available data and presented as aggregated estimates produced by a stated method. They are not audited findings, certifications, ratings or statements of fact about any government, institution, company or individual, and they are subject to revision without notice.
Assessment framework Under development
Equal weighting is a deliberate choice rather than a default. A government cannot offset absent safeguards with abundant compute capacity, so nothing here is allowed to buy its way past anything else.
Whether a government can design and fund AI policy against a stated national vision — including whether commitment is backed by assigned resources rather than published intent, and whether it engages internationally on a technology that does not respect borders.
Compute capacity and the enabling technical infrastructure that government and others can rely on over the long term, together with data that is sufficient, high quality, and able to move securely within and across borders.
Whether governance principles exist, are promoted, and shape how AI is developed and adopted — protecting rights and societal interests through the government's own practices, and giving those subject to AI decisions an adaptive route to compliance and redress.
Whether digital policy actually encourages testing AI against public-sector problems, and whether what proves effective is then scaled — evidenced in e-government delivery rather than in pilots.
Whether a domestic AI sector is mature enough to serve local demand and sustain long-term innovation, with the human capital for AI to diffuse to industry, researchers and civil society beyond the specialists.
Whether the government is managing the social, economic and environmental strain of widespread adoption, and actively monitoring the safety and security risks that grow as development and diffusion progress.
Research and publications Under development
The 2026 edition covers 195 governments across six equally weighted pillars, computed from published pillar data under a stated composite rule. Absent evidence is recorded as absent rather than estimated, and year-on-year movement is shown only where the source publishes it.
Also published
195
Governments assessed in the 2026 edition
69
Indicators, across 14 dimensions in six pillars
1 of 7
Registers currently backed by assessed data
CC BY-SA
License on the adapted national pillar dataset
Methodology questions, indicator-level data requests, briefings for policy and executive audiences, and media inquiries are handled directly by the assessment team.