This paper introduces an environment-driven, artificial intelligence model for sustainable policymaking in European countries, with a focus on Ukraine. It develops regional clusters using artificial neural networking; then, it dynamically optimises budgeting allocations. It is a hybrid, environment-driven model that clusters regionalised-data using Kohonen's self-organising map and optimises budget allocations using the simplex-modified distribution method (U-V MODI). Model benefits focus on regional public policies, environmental development, and core-periphery balanced growth. Results reveal an innovative plan that activates the participation of environmental stakeholders in public policymaking, reforms regions based on set sustainability criteria, and optimises regional funding.