Central and Eastern Europe in the AI Race: A New Index Reveals Regional Dynamics

AI Chamber, in partnership with The Recursive Media and with the support of Europe Cloud, recently launched the CEE AI Index 2026. This new research initiative was designed to measure the strategic AI readiness of countries across Central and Eastern Europe. The index, covering 11 nations, evaluates their structural ability to develop, deploy, and host artificial intelligence systems efficiently, safely, and within established governance frameworks.

The study's findings suggest that the region is more advanced in AI readiness than is often assumed. However, a growing divide is emerging between countries positioned to help shape Europe's AI landscape and those still building the foundations required to participate fully. An interesting insight is that success is not determined by country size alone; several smaller nations outperform larger economies through targeted investments in governance, talent, and digital infrastructure.

Technical Details and Differentiating Factors

The CEE AI Index analysis is based on 33 indicators and 363 data points, distributed across three main categories. The "Environment" category measures governance and digital infrastructure, crucial elements for data sovereignty and effective on-premise deployment. "Resources" evaluates talent and investment ecosystems, while "Deployment" examines AI adoption and research output.

Among the countries, several excellences stand out. Estonia distinguishes itself as the region's most institutionally mature AI ecosystem, combining advanced digital public services, strong enterprise adoption, and a high concentration of AI talent. Lithuania scored highly for open data governance and demand for AI professionals, while Slovenia stood out for research intensity and STEM capacity. Poland, while being the region's largest AI market, leads in research output, high-performance computing capacity, and workforce scale. These infrastructural elements, such as high-performance computing capacity, are fundamental for those evaluating the implementation of Large Language Models (LLM) on-premise, where the availability of adequate computational resources is a primary constraint.

Regulatory Context and Future Implications

One of the report's key conclusions is that governance has become a critical differentiator. While most countries in the region have introduced national AI strategies, only a smaller group has developed the institutional capacity required to implement them effectively. Estonia, Poland, and Lithuania recorded the strongest "Environment" scores, reflecting more mature governance frameworks, regulatory coordination, and robust digital infrastructure. Other countries continue to face challenges in translating policy ambitions into operational readiness.

The report also suggests that the European Union's AI Act could widen existing differences across the region. Countries with established governance structures may be better positioned to attract investment and support enterprise AI adoption, while others may face additional challenges in meeting regulatory requirements while simultaneously building domestic AI ecosystems. For those considering on-premise deployment, regulatory compliance and data sovereignty are crucial aspects that require solid infrastructure and governance.

Outlook and Collaboration Opportunities

Despite the differences in readiness levels, the index highlights a region characterized by complementary strengths rather than direct competition. No single country leads across all categories; instead, competitive advantages are distributed across research, talent development, infrastructure, governance, and market scale. The report also points to progress in countries including Hungary, Latvia, Slovakia, Bulgaria, and Croatia, each of which has developed specific capabilities ranging from experimentation infrastructure and tax incentives to technical expertise and education programs.

The publication of the CEE AI Index comes as AI sovereignty, infrastructure, and talent development move higher on policy and investment agendas across Europe. The report aims to provide policymakers, investors, and ecosystem builders with a clearer picture of where AI readiness is already operational and where further development is needed. Mark Boris Andrijanič, former Minister for Digital Transformation of Slovenia, noted that the findings highlight both the region's strengths and its continued funding gap, observing that Central and Eastern Europe remains underrepresented in discussions around major AI investment and development initiatives.