ceeindex - CEE AI INDEX

2026 Edition · Central & Eastern Europe

Mapping AI Readiness across CEE

CEE AI Index is the first index focused on assessing the ability of Central and Eastern European countries to develop, operate, and host AI efficiently, safely, and in a governed way. Taking into account regional context, we hope to provide policymakers, AI experts, businesses, investors and other ecosystem builders, a better understanding of regional strengths and weaknesses, enabling further advancement of AI innovation and adoption in the CEE.

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Overall score

Where does your country stand

What distinguishes this regional index is its focus on strategic AI readiness. CEE won’t benefit from measuring the capacity to compete with global players. For that reason, this index focuses on the readiness factor in the context of each CEE country's infrastructure, governance, funding, talent, and enterprises, with the aim of driving an AI-enabled ecosystem.

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Structural Architecture

The CEE countries haven't achieved their full AI potential

The index's highest overall score is 58.7, with a regional average near 44. No country in CEE is operating near the top of the scale. The gap runs through all three foundational pillars. This places the entire region in a structural "readiness" phase: the conditions for scaling AI are being built, not yet fully operational. That is both an honest constraint and a significant opportunity window for investment in those conditions.

Dominant Pattern

Most CEE countries built "the platform" before building what runs on it

Across the region, Environment (digital infrastructure, policy, governance) scores tend to outpace Resources (talent, subsidies, investment). Eight of eleven countries show a positive ENV to RES gap. This means countries have made progress on the structural prerequisites (connectivity, open data, regulation) but have not yet grown the human capital and investment ecosystems that would convert that infrastructure into active AI production. The platform exists; the ecosystem that fills it is still forming.

Scale Paradox

Small states consistently outperform their scale

Estonia (1.4M), Lithuania (2.9M), and Slovenia (2.1M) all rank in the top four overall. Poland (38M) ranks fourth. Size does not predict readiness in CEE, the ability to build and coordinate a coherent AI system does. Small states with deliberate, integrated policy postures and concentrated talent ecosystems are materially outperforming larger peers whose scale hasn't translated into equivalent intensity. This has implications for where targeted investment creates the most effect per unit.

Governance Gap

AI strategy isn't always a sign of governance execution depth

Seven of eleven CEE countries have a comprehensive, standalone, ethically-instructed, recently updated, or published AI strategy. For that matter, formal policy intent around AI is almost universal across CEE. What is genuinely scarce is the operational layer that should support that strategy: dedicated AI commissioners exist in only four countries (all appointed 2024–2025), operational regulatory sandboxes in three, and actively structured compute-access programmes in fewer still. The strategic intention gap has closed; the implementation infrastructure gap has not.

Infrastructure Dynamics

EU compute programmes are compressing the hardware gap, not the ecosystem gap

AI Factory participation, LUMI consortium access, and EuroHPC co-investments mean that even smaller or lower-scoring countries have documented pathways to shared compute capacity. This makes raw HPC availability a weaker differentiator than it was five years ago. What EU infrastructure does not provide is what still differs most: talent density, investment culture, and the policy intensity to orchestrate these

Pillars breakdown

Scores by pillars

The final CEE AI Index 2026 evaluates the strategic AI readiness of each country through three distinct lenses, each representing a critical stage of the AI lifecycle: Environment, Resources and Deployment. Check specific country rankings across each, and their side-by-side comparison.

Environment

Estonia leads. Bulgaria and Croatia trail significantly.

The Environment pillar covers AI-enabling governance structures and digital infrastructure. Estonia's lead rests on the region's most complete operational stack: governance, digital infrastructure, and public-sector readiness all move in the same direction. Poland and Lithuania follow closely, with strong enabling policies. Bulgaria and Croatia trail on nearly every Environment dimension, with the weakest infrastructure points in the index.

▲ Leader: Estonia 73 ▼ Trailing: Bulgaria 29

Resources

Slovenia leads. Latvia's talent gap is the region's starkest.

The Resources pillar measures AI-ready talent and the financial ecosystem. Slovenia's score is built on exceptional talent depth, the most targeted AI fellowship in the region, and the only fiscal incentive explicitly naming AI. Estonia and Lithuania follow, driven by AI professionals density and AI-focused funding. Mostly for the lack of investment instruments and talent density, Latvia has a resources score of just 19, the lowest in CEE.

▲ Leader: Slovenia 70 ▼ Trailing: Latvia 19

Deployment

Czechia and Poland lead. Slovakia and Croatia are stalled.

Deployment pillar captures enterprise AI uptake, R&D and education pipeline signals. Czechia and Poland lead on enterprise adoption depth and domestic AI production. Notably, Estonia (overall leader) ranks fifth here, mainly because of lower research scores. Slovakia and Croatia trail significantly — even where enabling conditions exist, real-world deployment remains limited.

▲ Leaders: Czechia & Poland ▼ Trailing: Slovakia 25

Comparison

Estonia leads across pillars. Latvia shows the starkest imbalance.

The heatmap reveals where each country's strengths and weaknesses lie across all three pillars simultaneously. Estonia dominates the governance (Environment), but trails on research (Deployment). Slovenia leads in talent and funding density (Resources) while lagging on business adoption (Deployment). Latvia's lowest Resources score is an outlier despite a solid Environment base. Poland and Czechia show the most balanced profiles.

▲ Most balanced: Poland ▼ Starkest gap: Latvia

Country profiles

Scores by country

Select a country to see its full AI readiness profile —
rank, pillar scores, radar chart, and expert assessment.

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Sub-pillars & Indicators

Scores by indicators

By analyzing 33 indicators across sub-pillars measuring sovereign compute, governance, specialized talent, funding, pivotal research, and commercial deployment, we benchmark the strategic AI readiness of the CEE-11 region.

Methodology

How we measure AI readiness

The goal of CEE AI Index is to identify regional strengths and gaps, moving beyond market dominance to measure how prepared these countries are to sustain a safe, and sovereign AI future.

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Scope

The CEE AI Index 2026 benchmarks the strategic AI readiness of 11 Central and Eastern European nations, namely: Bulgaria, Croatia, Czechia, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovakia, and Slovenia.

This is the first edition of the CEE AI Index, and our current geographic scope is due to the extent of the research and the availability of data for (un)select countries. In subsequent iterations, we hope to expand the scope to include all countries widely considered part of the CEE region.

💡 Data vintage

The overwhelming majority of data points (140 of 363) are dated 2025, making the research predominantly a snapshot rather than a historical compilation. Thirteen data points carry a 2026 date (mostly EuroHPC AI Factory status indicators updated in early 2026) and thirteen use 2020 data, which are the AI Patents figures, the oldest layer in the index.

Research

The index analyzes 33 indicators across three critical pillars representing the AI lifecycle:

Environment: Physical & digital infrastructure and regulatory frameworks.
Resources: Availability of specialized talent, R&D incentives and VC funding.
Deployment: Level of AI research and usage in business.

💡 Most differentiating indicators

The three highest standard deviations across countries belong to policy indicators: SRI Phase (52.2), Governance Body (50.5), and AI Strategy (47.4). These are binary or ordinal rubric-based measures, which naturally polarise scores. Conversely, the least differentiating indicators — Compute Subsidies, SME Adoption, AI in the Workforce — produce scores that cluster more closely together, suggesting these are areas where the 11 countries are converging rather than diverging.

Scoring

Scores are normalized on a 0–100 scale using a multi-layered weighting system, allowing us to compare very different measures consistently.

The indicators are selected and weighted based on their relevance to AI, their contribution to national AI capacity, and their data reliability. To ensure fairness, the index also balances Scale (absolute output) against Intensity (performance relative to GDP/population). This allows large economies like Poland and highly efficient ones like Estonia to be compared equitably.

💡 Indicator leadership

Every country leads on at least one indicator, so no country is completely outperformed across the board. Estonia leads the most (11 indicators), followed by Slovenia (9) and Poland (8). Latvia and Croatia lead on just one indicator each. Croatia also sits at the floor (score = 0) on more indicators than anyone else: 10 out of 33.

Results

The rankings are the result of the 33 indicators, the weights assigned to them, and the normalization methods applied. With strategic AI readiness focus, here is what a top performance in the CEE Index means:

Top-performing countries: Those most structurally ready to develop, operate, and host AI efficiently, safely, and in a governed way. They exhibit continuous, above-average performance in their foundational environments (infrastructure, policies, and regulations), possess strong research legacies, and have deep talent pools, making them highly attractive and stable hubs for AI integration.
Low-performing countries: Those least ready to sustain safe and efficient AI development and implementation. They exhibit continuous, below-average scores across foundational pillars, lacking clear policy and regulatory guardrails, compute infrastructure, a consistent research base, and talent pipelines necessary to integrate and scale AI, despite temporary uptake and business usage outliers. business usage outliers.

regional initiative

Behind the project

Europe Cloud is a premier technology partner and a one-stop shop for cloud innovation. Through partnerships with Google, AWS, and Microsoft, they provide expert consultancy, implementation, and 24/7 technical support from their specialized engineers. Clients also benefit from enhanced commercial flexibility.

AI Chamber is the leading business platform for SMEs advancing artificial intelligence across Central and Eastern Europe. It unites ambitious companies from diverse CEE markets to ensure their voice is heard in policy, support innovations, and accelerate growth. Through strategic insights, cross-border collaboration, and a strong policy presence, it empowers professionals shaping the region's AI future.

The Recursive is the relationship infrastructure for expanding tech ecosystems — the media, market intelligence, and market entry services that connect founders, investors, corporates, and policymakers across CEE and beyond.