THE USE OF AI AGENTS IN GREEN ECONOMY ANALYSIS: THE CASE OF THE MACEDONIAN ECONOMY
THE USE OF AI AGENTS IN GREEN ECONOMY ANALYSIS: THE CASE OF THE MACEDONIAN ECONOMY

Summary/Abstract: The transition to a Green Economy is a critical imperativefor the Western Balkans, particularly for North Macedonia, which faces signif-icant environmental challenges, including high carbon intensity and relianceon fossil fuels. However, the first point of this transition is often the existenceand reliability of datasets, limited technical capacity for forecasting, and datalatency. This paper explores the transformative potential of Artificial Intelli-gence (AI) Agents—autonomous systems capable of analyzing Green Economytime series data. Specifically, the study focuses on Greenhouse Gas (GHG)emissions from 1990 to 2019. Utilizing a framework built on Python (Pandas),LangChain, and the Ollama LLM (gpt-oss-20b), we deployed AI agents to per-form both descriptive and predictive analytics. The results demonstrate that AIagents can successfully autonomously query historical data to identify criticallow-emission periods and generate numeric forecasts for 2025 across six keysectors: Total Emissions, Energy, Industrial Processes, Agriculture, Forestry,and Waste. The study validates the hypothesis that AI agents can serve as ro-bust tools for evidence-based climate governance, offering a pathway towardmore adaptive and real-time environmental policy formulation.

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