OPTIMIZING GREEN PUBLIC INVESTMENT THROUGH AI: A SMART APPROACH TO CLIMATE BUDGETING

Abstract

Our study investigates the impactful potential of Artificial Intelligence (AI) in optimizing green public investment decisions, particularly within climate budgeting, sustainable infrastructure planning, and smart city initiatives. Using methods such as advanced simulation, predictive analytics, and real-world smart city case studies (Singapore, Amsterdam, Stockholm, Tashkent), this research demonstrates how AI can enhance the efficiency and effectiveness of resource allocation by simulating complex environmental and economic trade-offs. The ability of AI to navigate these multi-objective optimization problems represents a significant advancement beyond traditional, linear budgeting approaches, enabling a more holistic and systemic approach to climate finance. Findings indicate that AI-driven approaches can lead to significantly improved CO₂ reduction, higher return on investment, and faster impact realization compared to traditional budgeting methods. The report also addresses critical considerations such as data reliability, algorithmic transparency, and ethical governance. Policy implications highlight the imperative for governments to integrate AI into their climate finance frameworks to foster a more resilient, sustainable, and economically viable future.