Policy Brief

Policy Brief Advancing Climate Adaptation through AI-Driven Early Warning Systems and South-South Cooperation Author: Dorcas Chepkirui, Date: November 2025 Keywords: Climate Adaptation, Artificial Intelligence (AI), Early Warning Systems, Technical Cooperation, Resilience, South-South Cooperation Key Messages 1. AI-powered Early Warning Systems (EWS) are a promising solution for strengthening climate adaptation, but face implementation barriers in many Global South countries. 2. South-South cooperation, built on mutual learning and local innovation, can drive scalable, ethical, and context-sensitive AI adoption. 3. Embedding AI into national climate frameworks, coupled with inclusive community design and digital capacitybuilding, can significantly enhance resilience to climate shocks. Executive Summary As climate shocks intensify, vulnerable countries in the Global South face mounting challenges in anticipating and managing risks. Artificial Intelligence (AI)–driven Early Warning Systems (EWS) offer transformative potential for strengthening climate adaptation through timely forecasting and improved disaster preparedness. This policy brief explores how AI innovations, when embedded in inclusive and ethical frameworks, can enhance climate resilience. Grounded in South-South cooperation and guided by Innovation Diffusion Theory, it highlights how peer learning, shared digital infrastructure, and community-led innovation can accelerate adoption. Mainstreaming AI through ethical governance, digital infrastructure, and cooperative partnerships can radically enhance climate resilience in the Global South. Policy Context Climate-related disasters such as droughts, floods, and heatwaves are increasing in frequency and intensity. While AIpowered EWS can transform early warning capabilities, adoption remains uneven due to limited infrastructure, weak coordination, ethical concerns, and exclusion of local voices. South-South and triangular cooperation, defined by peer learning, joint innovation, and shared governance, provides a compelling alternative to traditional top-down approaches. By fostering shared learning, co-creation, and equitable access to technology, such cooperation can promote scalable and context-sensitive AI adoption. Barriers to Equitable AI Adoption Barrier Description Ethical and governance gaps Algorithmic bias, data privacy risks, and lack of regulatory oversight Weak institutional coordination Fragmented governance structures hinder cross-sectoral climate planning. Community exclusion Minimal participation of local actors undermines the usability and legitimacy of AI tools. Digital divide Limited access to the internet, electricity, and digital infrastructure hinders AI uptake, especially in rural areas. Policy Recommendations Policy Focus Strategic Action Integrate AI into National Adaptation Plans (NAPs) Mainstream AI applications in priority sectors (agriculture, water, urban planning Establish ethical AI guidelines Develop standards with nited Nations Environment Programme (UNEP) and regional partners to ensure transparency, equity, and accountability. Strengthen South-South cooperation Create AI innovation hubs, joint research and development platforms, and peer training networks to exchange knowledge and best practices. Centre community participation Co-design AI tools with local users to enhance trust, relevance, and accessibility Build digital capacity and infrastructure Invest in human capital, open data systems, and regional AI labs to enable scalable, high-impact solutions Case Studies at a Glance Innovation Diffusion Theory: A Framework for Climate Tech Adoption Everett Rogers’ Innovation Diffusion Theory explains how innovations spread through societies. Its five elements, relative advantage, compatibility, complexity, trialability, and observability help assess the adoption potential of AI tools. In the context of AI-driven climate adaptation, the process typically unfolds through three phases, the knowledge and persuasion phase, the decision and implementation phase and the confirmation stage. During the knowledge and persuasion stage, peer exchange and capacity-building initiatives enhance awareness and willingness to adopt innovative tools. The decision and implementation phase follows, where strong technical partnerships and localized pilot projects help tailor AI applications to local needs. Finally, in the confirmation stage, policy integration and welldocumented success stories reinforce continued use and long-term sustainability. South-South cooperation accelerates adoption by sharing evidence, reducing risk, and building local champions. International technical cooperation helps accelerate this process by lowering risks, sharing evidence, and building local champions for innovation. Conclusion AI offers powerful opportunities to reshape climate adaptation, only if it is deployed equitably, ethically, and collaboratively. Governments and development partners must urgently integrate AI into climate policy and governance. Technical cooperation across the Global South must be deepened to ensure mutual learning, locally led innovation, and climate justice. The future of climate resilience is digital and must be inclusive. Country AI Use Case Impact India Deep learning models for monsoon forecasting Improved agricultural preparedness and reduced losses for millions of farmers Kenya Drought monitoring and livestock movement using mobile-based AI alerts Increased pastoralist resilience, real-time decision-making support Brazil AI-enhanced satellite tracking of illegal deforestation Enabled rapid enforcement and conservation through real-time alerts About the Author Dorcas Chepkirui is a public policy and development professional with expertise in environmental sustainability, humanitarian affairs, and climate change. She has worked in public administration, project coordination, and research across Kenya, Türkiye, and Europe, contributing to initiatives in education reform, refugee integration, and local governance. Currently pursuing a PhD in Political Science and Public Administration at Sakarya University, Turkey, her research explores climate policy, institutional governance, and adaptation strategies in African countries. Dorcas is committed to advancing inclusive, evidence-based approaches to climate adaptation and sustainable development. Email: dorcascchepki[email protected] LinkedIn: linkedin.com/in/dorcas-chepkirui-261ab9130