AI-Powered Climate Modelling: Predicting Tomorrow, Today

Introduction
The AI-Based Climate Modelling Market, valued at USD 242 million in 2023, is projected to reach USD 1,715.2 million by 2032, growing at a strong CAGR of 34.32%. Rising extreme weather events and the urgent need for disaster preparedness are driving demand for AI-powered tools. From deep learning models enhancing long-range predictions to AI-physics hybrids boosting accuracy, industries like energy, agriculture, and insurance are adopting climate AI at scale.
With governments embedding these models into sustainability and ESG frameworks, could AI soon become the backbone of global climate action?
Key Players
The market is led by tech and climate innovators such as IBM (Environmental Intelligence Suite), Microsoft (Planetary Computer), Google (Earth Engine), AWS (ASDI), Oracle, and Tomorrow.io. Niche players like Jupiter Intelligence, Cervest, and ClimateAi specialize in climate risk intelligence and predictive analytics for enterprises.
With Big Tech offering massive computing power and startups delivering hyper-localized solutions, which group do you think will lead the next wave—global tech giants or climate-focused disruptors?
Segmentation
By component, software dominated (82% in 2023), thanks to its scalability in real-time forecasting, while services are set to grow fastest as firms seek customized advisory. Deployment-wise, cloud leads with 65% share, but on-premises solutions are gaining traction in sectors like defence and energy for security-sensitive forecasting. By technology, machine learning currently leads, while deep learning is the fastest-growing for long-range, high-resolution climate simulations. Regionally, North America holds 36% share, while Asia-Pacific is expected to grow fastest, fuelled by smart city projects and disaster resilience investments.
Could Asia soon become the global hub for AI-powered climate intelligence?
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