Институт За Политичке Студије

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QUANTIFICATION OF GEOPOLITICAL FACTORS VIA ARTIFICIAL INTELLIGENCE

Сажетак

The contemporary security environment, characterized by extreme volatility and a structural transition towards a multipolar geopolitical paradigm, has exposed the severe analytical and operational limitations of traditional bureaucratic models of strategic planning. The subject of this paper is a theoretical and methodological analysis of the possibilities for integrating artificial intelligence systems into the process of continuous security risk assessment. The research goal is to present the conceptual architecture of the ARES model (AI-Driven Risk & Environment Strategy) as an innovative instrument that enables the quantification of geopolitical, geoeconomic, and demographic factors into measurable algorithmic inputs. By applying Markov Decision Processes and deep learning algorithms, the ARES model enables advanced simulations (AI wargaming) that filter out bureaucratic biases. Through the application of modeling, analysis, and synthesis methods, the paper indicates that the implementation of predictive analytics within the state apparatus is sustainable only through the normative synergy of the ISO 31000 and ISO/IEC 42001 standards. The results show that the intersection of classical geopolitical methodology and predictive analytics (AI wargaming) substantially shortens the state’s reaction time to hybrid threats. It is concluded that the algorithmization of risk assessment does not abolish doctrinal sovereignty but rather strengthens it, with the mandatory condition of retaining the Human-in-the-Loop mechanism in strategic decision-making.

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