AI-Enabled, Doctrine-Compliant Decision Superiority for CBRN and Hybrid Threat Environments

Abstract

: Contemporary CBRN threats increasingly emerge within hybrid, multi-domain environments characterised by ambiguity, distributed data streams, and compressed decision timelines. Existing NATO-compliant systems remain largely reactive, deterministic, and dependent on human-initiated processes, generating decision delays of 20 – 45 minutes — well beyond the critical 10 – 15-minute early-warning window required to prevent mass casualties. The study identifies five major operational capability gaps and proposes the AI-Enabled CBRN Decision Superiority System (AI-CDSS), a six-layer, doctrine-compliant architecture combining predictive analytics, high-resolution environmental modelling, civil-military data fusion, and explainable AI (XAI). Its core innovation is the trust-centred integration of advanced technologies within a framework that embeds NATO ATP-45 decision logic as formal finite-state machines, quantifies uncertainty through calibrated confidence intervals, and preserves human-in-the-loop override authority. Simulation-based projections demonstrate a 60 – 80% reduction in decision latency, a 66% decrease in hazard-zone area error, and removal of manual doctrinal translation steps.