The study aims to develop a dynamic management structure to enhance investment activity by minimizing the brain drain and developing human capital as a key driver of sustainable economic growth. A multilevel model linking migration flows of young scientists, resource potential components, scientific and technical potential, and macroeconomic dynamics has been constructed based on a synthesis of agent-based modeling and system dynamics. The use of distributed lag models, compositional and recursive approaches, neural network forecasting, and scenario analysis revealed significant negative effects of emigration on key development resources that increase over time. A direct but asymmetric relationship between resource potential and growth has been revealed: its recovery rate is twice as low as the rate of destruction under the influence of shocks. The results substantiate the imperative of developing a comprehensive proactive public policy for using open innovation mechanisms and network interaction. The proposed dynamic structure serves as a tool for the formation of adaptive mechanisms of state regulation aimed at transforming human capital into the main source of investment activity and sustainable development in the context of global challenges.