Managing Structural Exposure in the Arctic: Greenland as an AI-Strategic Node in Great-Power Interaction

This policy brief applies the AI-Strategic Node Index (AI-SNI) as a diagnostic lens to examine Greenland as a structurally significant node in contemporary great-power interaction in the Arctic. Rather than treating Greenland as a strategic actor or policy subject, the brief analyzes how Greenland-linked infrastructures are embedded within multiple AI-mediated systems, including strategic early-warning and missile detection architectures, high-latitude maritime and air surveillance, global climate and sea-level modelling frameworks, and emerging resource–data–energy coupling pathways. AI-SNI diagnostics indicate that the Greenland case occupies a Tier 3 exposure regime, reflecting relevant structural centrality without implying ordinal risk ranking, strategic superiority, or policy priority. The analysis highlights high functional centrality in sensing and decision-loop timing, moderate leverage within globally shared predictive models, and latent future optionality contingent on governance credibility. The primary binding constraint identified is infrastructure–governance asymmetry, arising from fragmented control, auditability, and escalation arrangements across interacting actors. This brief is designed for Track-2 diplomacy and non-official strategic dialogue. It does not assign policy mandates, advocate strategic escalation, or attribute structural class. Instead, it illustrates how AI-mediated systems generate shared exposure regimes that precede political consensus and require governance-oriented discussion rather than competitive positioning. This release constitutes the first public publication of EPINOVA Policy Brief PB-03 and complements prior AI-SNI methodological and node-level case studies.