AI-Driven Climate Risk Intelligence As Critical Infrastructure For Society

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Authors: Naga Venkateswar Palaparthy
Cited by: 0

Abstract

Climate change imposes operational complexities that require measurable risk intelligence at the residential, business, and governmental levels. Conventional approaches to climate evaluation are unaffordable, restricted, and unstandardized. The article demonstrates the effectiveness of cloud-native, artificial intelligence-powered climate risk solutions as digital public infrastructure. The solutions synthesize climate data feeds, catastrophe history, satellite imagery, and climate models to produce continuously refreshed geospatial risk analyses. The system maps environmental datasets to actionable intelligence, empowering preemptive resilience strategies instead of post-event crisis response. Their contributions lie in democratizing access to advanced climate analysis, promulgating risk quantification paradigms, and stabilizing financial markets via portfolio-level risk assessment of exposure. Evaluation illustrates their societal effectiveness through fair distribution of risk intelligence, data-driven policy design, and clear capital allocation practices. Designed to handle tens of millions of geospatial queries in under a second, without compromising analytic fidelity to floods, fires, wind, heat, and drought risk models, the system demonstrates effectiveness in migrating high-barricade, proprietary solutions to public infrastructural status, thereby innovating novel paradigms to prospect and respond to climate risks in the areas of urban planning, financial, and disaster resilience solutions.

Fields of Study & Subjects

Disaster Management and Resilience Flood Risk Assessment and Management Energy and Environmental Systems

Publication details

Journal / source
Journal of International Crisis and Risk Communication Research
Publication date
10 February 2026
Language
EN