UN Climate Change News, 11 July 2025 - A new technical paper released by the Technology Executive Committee (TEC) under the UNFCCC Technology Mechanism explores how Artificial Intelligence (AI) can serve as a powerful enabler of climate action in developing countries most vulnerable to climate impacts.
The TEC Chair, Dietram Oppelt, launched the Committee's latest technical paper at the AI for Good Summit in Geneva yesterday. Developed in collaboration with the United Nations Industrial Development Organization, and with the support of the Korea International Cooperation Agency, the paper is part of the Technology Mechanism's #AI4ClimateAction Initiative. It provides a comprehensive overview for policymakers, practitioners and researchers navigating the opportunities, risks and challenges of deploying AI for climate mitigation and adaptation in developing countries.
AI as a Tool for Climate Action
AI technologies offer significant potential to reduce greenhouse gas emissions. For instance, AI can help minimize energy waste, optimize energy consumption and distribution, and identify emission hotspots in industrial processes. AI-powered energy management systems can improve grid efficiency, forecast power demand, and optimize the deployment of renewable energy sources such as solar and wind. Similarly, AI tools can analyze transportation data to optimize traffic flow and route planning, reducing fuel consumption and emissions.
Additionally, AI also offers promising applications when it comes to adapting to the impacts of climate change. It can strengthen early warning systems by predicting extreme weather events such as hurricanes, floods and droughts, enabling proactive disaster risk management. AI-driven urban resilience planning can help identify infrastructure vulnerabilities and optimize land use. When combined with satellite imagery, AI can also support biodiversity conservation, sustainable water use, and land restoration efforts.
Risks and Challenges of Using AI for Climate Action in Developing Countries
Despite these benefits, the paper highlights that bias and inequity in AI systems also present serious risks. If algorithms are not designed inclusively, they can perpetuate social inequalities and undermine trust. Additionally, the energy and water consumption of AI systems raises sustainability concerns, particularly in regions already facing resource constraints.
The paper also warns that many developing countries face significant barriers to adopting AI-driven climate solutions. Limited digital infrastructure - including unreliable internet connectivity, inadequate computing power, and capacity shortages - hinder the effective deployment of AI systems.
Moreover, developing countries often lack access to high-quality, comprehensive climate data essential for training AI models and supporting robust, data-driven decision-making. Without reliable data-sharing frameworks and cybersecurity measures, AI outputs can be inaccurate or vulnerable to misuse.
Recommendations for Realizing AI's Potential
To unlock the benefits of AI for climate action in developing countries - especially Least Developed Countries and Small Island Developing States - the paper outlines a set of recommended priority actions:
- Address the digital divide by investing in infrastructure and AI capacity-building programmes that empower local experts and institutions.
- Enhance data availability and access through improved climate data collection and open-data initiatives to support AI model development and deployment.
- Strengthen AI governance under the UNFCCC by creating regulatory frameworks that promote transparency, fairness, accountability and ethical AI adoption.
- Tackle gender bias and social inequalities by designing AI systems with inclusive approaches to deliver equitable climate benefits.
- Manage AI's resource consumption by promoting energy- and water-efficient AI systems to ensure sustainability.
- Foster global collaboration by strengthening cooperation between governments, UN agencies, the private sector, academia, and civil society to share knowledge, align standards, and address regulatory gaps.
Implementing these recommendations can help developing countries harness AI as a strategic tool to advance climate action at scale. Strengthening digital infrastructure, closing data gaps, and adopting robust governance frameworks will not only build local capacity but also encourage innovation and collaboration.
This will help ensure that all countries - especially those most vulnerable to climate change - can participate fully in global climate efforts while addressing their unique challenges.
