Kathmandu - As climate change intensifies the frequency and impact of floods, heatwaves, storms, droughts, and coastal hazards, artificial intelligence (AI) is increasingly being positioned as a critical tool to support climate adaptation and disaster risk reduction worldwide.
According to recent insights highlighted by the United Nations Office for Disaster Risk Reduction (UNDRR), AI-driven technologies are now being applied across multiple sectors to help governments and communities anticipate risks, plan responses, and build long-term resilience. From climate modelling to early warning systems, AI is reshaping how societies prepare for and respond to climate-related disasters.
Strengthening Early Warning and Climate Planning
One of the most immediate contributions of AI lies in disaster early warning systems. Machine learning models can process vast amounts of meteorological, hydrological, and satellite data in real time, enabling faster and more accurate forecasts of extreme weather events. Such systems can provide earlier alerts for floods, cyclones, heatwaves, and landslides-critical in saving lives, particularly in disaster-prone regions of Asia and the Pacific.
AI is also improving climate modelling and long-term planning. By analysing complex climate patterns, AI helps policymakers better understand future risks and design adaptation strategies for vulnerable regions, including rapidly urbanising cities and low-lying coastal zones.
Supporting Ecosystems, Food Systems, and Water Security
Beyond disaster warnings, AI is being used to monitor biodiversity, manage marine and coastal ecosystems, and predict land-use changes that can increase environmental vulnerability. Remote sensing combined with AI enables continuous observation of forests, wetlands, coral reefs, and agricultural lands, offering early signals of degradation or stress.
In the agri-food sector, AI-based tools are helping optimise crop production, irrigation, and resource use-an important step as climate variability threatens food security. Similarly, AI-supported water management systems can improve allocation, reduce wastage, and enhance resilience during droughts and floods.
Urban Resilience and Infrastructure Planning
Cities, which concentrate both populations and risks, are another focus area. AI is being applied to urban resilience planning, helping authorities assess infrastructure vulnerabilities, plan climate-resilient housing, and manage energy and transport systems more efficiently.
Concerns Over Equity, Data Bias, and Access
Despite its promise, experts caution that AI is not a universal solution. UN agencies and climate advocates warn that unequal access to digital infrastructure, limited data availability in developing countries, and algorithmic bias could widen existing inequalities if not addressed carefully.
Ensuring that AI-based innovations benefit those most vulnerable to climate impacts-including low-income communities, rural populations, and least developed countries-requires deliberate policy choices. Bridging the digital divide, strengthening local data systems, and promoting transparent and inclusive governance are seen as essential steps.
A Tool, Not a Substitute
Global climate institutions emphasise that AI should complement, not replace, human decision-making, local knowledge, and community-based disaster risk management. When used responsibly, AI can enhance preparedness, efficiency, and adaptation outcomes-but without strong safeguards, its benefits may remain uneven.
As climate risks continue to escalate, the challenge for governments and development partners will be to harness AI’s potential while ensuring it supports inclusive, ethical, and people-centred climate action.
