This project aims to strengthen Turkmenistan’s human capital planning by establishing a coherent, data-driven system that aligns education, skills development, and workforce planning with the country’s economic diversification and digital transformation priorities. The initiative will identify current and future skills needs, analyze gaps between education outcomes and labor market demand, and assess institutional and financing constraints affecting human capital development.  

The project also aims to establish in Turkmenistan an institutional mechanism for leveraging the demographic dividend as a driver of accelerated economic growth, increased labor productivity, and the development of new high value‑added sectors. The system should ensure not only the alignment of education with current labor market demand but also support the creation of future economic niches through the strategic development of human capital. The project should contribute to building a culture of forecasting, interagency planning, and data‑driven decision-making within national governing institutions, including strengthening capacities for conducting foresight sessions, interpreting analytics, and using forecasts in practical policymaking. 

It will support the development of an analytical model and governance framework for evidence-based skills planning, while piloting a prototype of an AI-enabled digital platform to support data-driven decision-making. By addressing systemic gaps in skills governance and institutional capacity, the project will contribute to more effective workforce planning, improved alignment between education and employment opportunities, and the advancement of a knowledge-based, innovation-driven economy in Turkmenistan. The results of the project should serve as a practical tool for determining enrollment quotas, revising the list of specialties, updating educational programs, identifying skills shortages and risks of oversupply of specialists, as well as for substantiating decisions on the development of new economic sectors based on data and forecasts.