GAIA Country AI-Economy Briefing

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Economic context

The macro backdrop to AI adoption — World Bank indicators.

Source: World Bank WDI (latest available year per indicator).

Innovation & capability

The capital-and-capability base for AI — R&D, research workforce, patents, high-tech trade.

Source: World Bank WDI. AI-specific private investment (Stanford HAI) is US/China-concentrated; these give universal coverage.

How the country uses AI

Use-case split and collaboration style, versus the global average.

Use-case split

Work · Personal · Coursework — vs. global

Collaboration style

How people work with AI — vs. global

Readiness & positioning

IMF AI Preparedness sub-indices, and where the country sits on readiness vs. adoption.

AI-preparedness profile

IMF AIPI sub-indices (0–1)

Readiness × adoption

This country vs. all others

Compute & infrastructure

Domestic data-center footprint and the compute-dependency signal.

Facilities from OpenStreetMap; capacity from GAIA's curated layer. Full compute report on the Data Centers page.

Key takeaways

Auto-generated from the data for this country.

For more information

The full GAIA Country Report

This briefing is the free view. The full report adds the decision-grade layer:

🔒Sector-by-sector exposure & employment at risk▓▓
🔒Compute-dependency index & energy-grid analysis▓▓
🔒Skills-gap & reskilling priorities▓▓
🔒Policy-lever options & peer benchmarking▓▓
🔒Fiscal & investment scenarios (3–5 yr)▓▓
🔒Bespoke briefing & workshop for your team▓▓
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Sources & method. Adoption & collaboration: GAIA country data (Anthropic Economic Index, Feb 2026). Readiness: IMF AI Preparedness Index. Compute: OpenStreetMap coverage + GAIA curated capacity layer. "Three things to know" are generated from thresholds on the underlying data. Figures are indicative measures for briefing purposes; the full report carries full provenance, uncertainty, and sector detail.