Strategic Focus: AI Innovations In Physical Climate Risk Software
28 Oct, 2026
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Executive Summary
Physical climate risks remain challenging to quantify, due to persistent gaps in both climate data and modelling approaches, which weaken adaptation and investment decisions. Physical climate risk software vendors are embedding AI to bridge these gaps by downscaling global climate models (GCMs), enriching asset and entity data, and translating technical outputs for decision-makers. However, vendor approaches vary widely, from physics-first models that apply AI selectively, to platforms that embed AI across key workflows. This variation makes the level of AI in a platform a procurement decision in its own right. Geared towards risk and resilience leaders looking to invest in physical climate risk solutions, this report outlines how vendors integrate AI, the various use cases where AI adds most value and the governance measures vendors apply – helping firms select a solution that matches their tolerance for AI-driven outputs.Firms are using AI to more precisely identify, assess and interpret physical climate risks
Vendors take varying approaches to integrating AI, from selective application to full platform automation
Physical climate risk use cases embed AI to enhance data completeness and support risk analysis, but decision-making remains grounded in climate science
AI remains constrained in risk quantification and analytics use cases, with vendors governing their applications carefully
Figure 1. Different vendor approaches to integrating AI into physical climate risk platforms
AXA, Cambridge Econometrics, Climate X, Coordinated Regional Climate
Downscaling Experiment (CORDEX), Copernicus, Cornell University, Correntics, Coupled Model Intercomparison
Project (CMIP), First Street, Google, International Electrotechnical
Commission (IEC), International Organization for
Standardization (ISO), Jupiter Intelligence, Mitiga Solutions, Risilience, Trex Analysis, US National Institute of
Standards and Technology (NIST), XDI (Cross Dependency
Initiative)
About the Authors

Mahum Khawar
Analyst
Mahum is an Analyst at Verdantix, specializing in AI integrations within risk management software and operational resilience. She advises technology buyers and software vendor...
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Luis Niño
Senior Manager
Luis leads the risk management research team at Verdantix, focusing on how regulatory requirements intersect with GRC strategies and delivering insights that help clients unde...
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