2026 Edition · 190 governments assessed · 47 indicators
Now in its 2nd edition, the Global AI Index™ assesses 190 governments across four equally weighted pillars spanning capability and governance. The complete indicator dataset is published alongside the report.
Synthesized from public data · 10 August 2026 Full rankings →
The 2026 Index
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Global AI Index synthesis methodology. Scores are produced by the Index from publicly available data, normalized to a common 0–100 scale and aggregated across four equally weighted pillars. Synthesis current as of . Full derivation, sources and indicator weights are set out in the methodology.
Overview
Published strategy is now near-universal among assessed governments and no longer distinguishes between them. The Global AI Index™ therefore scores 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 Index™ has 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.
Ninety percent of assessed governments now maintain a published AI strategy. Substantially fewer have established 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 Index measures the distance between those two positions.
The 2026 edition assesses 190 governments against 47 indicators drawn from 21 sources, 14 of which are primary. Where a government has not supplied evidence, the indicator is recorded as absent rather than estimated, and the omission is disclosed on the country profile. 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.
Assessment framework
Equal weighting is a deliberate methodological choice rather than a default. A government cannot offset absent safeguards with abundant compute capacity.
Whether a named body owns AI policy, holds a recurring budget, and has authority to commission and withdraw systems across departments. Coordination that exists only on an organization chart does not score.
Compute capacity under the government's own legal control, data infrastructure, interoperability standards, and the connectivity on which public services depend.
Specialist and general capability within the public workforce, the routes by which it is recruited and retained, and the domestic research base available to government.
Enforceable rules, independent oversight with the staff to exercise it, transparency obligations, and a redress mechanism that demonstrably overturns decisions.
Research and publications
The 2nd edition assesses 190 governments against 47 indicators across four equally weighted pillars. This edition revises the methodology to weight enforcement evidence above the existence of a legal instrument, and to record absent evidence as absent rather than estimating it.
Read the report
Also published
190
Governments assessed in the 2026 edition
47
Indicators, 14 of which draw on primary evidence
2nd
Edition, published annually since 2025
21
Public data sources synthesized into the composite
Methodology questions, indicator-level data requests, briefings for policy and executive audiences, and media inquiries are handled directly by the assessment team.