Skills anticipation and labour market intelligence (LMI) have become central to education, training and employment reforms across Central Asia. As Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan pursue economic diversification and modernise their vocational education and training (VET) systems, the ability to anticipate emerging skills needs and to translate that knowledge into policy and practice is increasingly recognised as a foundation for effective, demand-driven reform.
Since 2020, the European Training Foundation (ETF), through its Skills Lab initiative, has worked with partner countries to foster a culture of skills anticipation, acting as an observatory for skills demand and bringing together a global community of practitioners under the ETF Skills Lab Network of Experts, established in October 2021. In Central Asia, this agenda has been reinforced through the EU-funded DARYA programme (Dialogue and Action for Resourceful Youth in Central Asia, 2022–2027), under which Kazakhstan and the Kyrgyz Republic have rolled out new graduate and employer surveys, and countries across the region are jointly developing occupational standards and piloting the recognition of skills acquired outside formal education.
Despite this progress, many national labour market information systems (LMIS) in the region remain reliant on fragmented, largely administrative data sources, with limited integration of employer and graduate surveys, online job vacancy analytics and other emerging ‘big data’ sources into a coherent and institutionalised system. As ETF guidance on LMIS design underlines, there is no single blueprint for an effective architecture: institutional arrangements must be adapted to each country’s governance context and statistical capacity, while systematically linking data producers (statistical offices, public employment services and education authorities) with policymakers and other data beneficiaries1.
This regional focus is reinforced by EU-level skills anticipation infrastructure that offers relevant methodological reference points: Cedefop’s Skills Forecast, its Short-Term Anticipation of Skills trends and VET demand (STAS) tool, and Skills-OVATE, its online job vacancy analysis platform, together illustrate how harmonised, comparable data and administrative and big-data sources can be combined into a standing EU-wide skills intelligence infrastructure2.
Recent Central Asian evidence underscores the stakes: the World Bank’s 2026 Kazakhstan Economic Update highlights persistent gaps in foundational and job-relevant skills as a constraint on productivity, while its 2024 report on jobs in Kazakhstan and earlier regional jobs, skills and migration surveys in the Kyrgyz Republic, Tajikistan and Uzbekistan point to continuing skills mismatches and the importance of better labour market data for policy design. Furthermore, the ILO’s ongoing work on labour market information systems and public employment services across the region further underlines the institutional dimension of building sustainable LMI systems.
Further Reading:
The Future of Skills in ETF Partner Countries (2024), ETF’s multi-faceted approach to skills anticipation, including Big Data analysis; Education, Skills and Employment: Trends and Developments 2024, annual cross-country monitoring report covering Central Asia; DARYA (2022–2027). All at etf.europa.eu.
Big Data for Labour Market Intelligence (2023)
How to translate skills demand evidence into effective policies? (2026)
1European Training Foundation, Labour Market Information Systems (LMIS) – guidance on LMIS institutional architecture and governance options, etf.europa.eu
2Cedefop, Skills Forecast (projections to 2035), Short-Term Anticipation of Skills trends and VET demand (STAS), and Skills-OVATE online job vacancy analysis tool, cedefop.europa.eu
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