related conflicts. It analyses the relationship between climate change and the escalation of security risks while exploring the epistemological shift introduced by AI-driven systems in modelling climate risks and managing uncertainty. The study adopts an analytical and foresight-based approach, employing an interdisciplinary framework that integrates climate studies, AI, security studies and governance through a critical analysis of the relevant literature, explanatory models and future scenarios. The findings demonstrate that AI represents a profound epistemological transformation in climate risk analysis by shifting conflict management from reactive response to anticipatory governance through probabilistic models capable of capturing the complexity of environmental and societal interactions. The study further argues that the strategic value of smart climate modelling extends beyond improving risk prediction to reshaping decision-making processes and strengthening early warning systems. At the same time, it highlights the legal, ethical and geopolitical challenges associated with algorithmic governance, data sovereignty and equitable access to climate information. Finally, the study proposes the concept of algorithmic climate security as an analytical framework for understanding the evolving relationship between technology, climate and global security, emphasising that the effectiveness of these models ultimately depends on the establishment of transparent and equitable governance frameworks capable of promoting sustainable climate security. Keywords: smart climate modelling, climate artificial intelligence (climate AI), algorithmic climate security, resource-related conflicts, proactive risk governance.
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