Artificial Intelligence: A Game Changer for Sustainability In recent years, climate change has emerged not merely as an environmental issue but as a critical challenge shaking global economic and social structures. Amidst this, Artificial Intelligence (AI) is gaining significant attention and prominence in climate change response strategies. This signifies a crucial turning point, extending beyond mere technological innovation to transform the behavior of governments, businesses, and individuals. According to the International Energy Agency's (IEA) 2025 report, AI is projected to play a pivotal role in various areas, including grid balancing, industrial process optimization, and climate-related data integration. Can AI truly be the key to solving the climate change equation? It is necessary to examine the importance and potential of AI in addressing climate change. The World Economic Forum (WEF) has identified AI as one of the few technologies capable of significantly bending the carbon emissions curve downwards before 2030. This indicates that AI has evolved beyond simple task automation to become a core infrastructure for institutional decision-making. For businesses, reducing carbon emissions is directly linked to profitability. According to a report published by CDP (formerly Carbon Disclosure Project), up to 75% of large corporations' greenhouse gas emissions originate from their supply chains. These are referred to as 'Scope 3 emissions,' representing indirect emissions that a company does not directly control but occur throughout its value chain. This illustrates why the implementation of AI-powered intelligent systems across the entire supply chain is crucial, going beyond mere task automation. In particular, AI-driven climate data analysis has become an indispensable tool for the design and implementation of climate policies. Net0, a company operating an AI-powered climate data platform, processes over 1.2 million invoices monthly to provide continuous and auditable emissions information. Without AI technology, such vast amounts of data would have to be processed manually, leading to significant losses in terms of time and cost. Sofia Fominova, co-founder of Net0, emphasized, "AI plays an essential role in enabling us to process climate data in real-time and gain clear, actionable insights." She particularly stressed that manual climate data collection is inefficient at corporate and governmental scales, and AI is the only way to solve this problem. What is the current status of AI adoption by Korean companies and government? What about the situation in Korea? While Korea has actively committed to achieving carbon neutrality by 2050, there are observations that AI utilization is not yet as active compared to developed nations. Major domestic corporations are only now beginning to seriously discuss the introduction of AI-based carbon management systems. Companies like Samsung Electronics and LG Electronics are developing solutions for energy efficiency and sustainability, and some large corporations are piloting AI technology to track carbon emissions across their supply chains. However, extending this across the entire supply chain and encompassing small and medium-sized partners still appears to require significant time and investment. Consequently, there is an argument that cooperation between the government and businesses needs to become closer. From an international perspective, AI-driven climate change response is already yielding tangible results in several developed countries. Fominova emphasizes that AI is a powerful tool that helps optimize energy use, improve supply chains, and predict and prepare for the impacts of climate change. She particularly points out that without AI, it is virtually impossible for businesses and governments to process and analyze the scale of data required to achieve climate goals. This offers significant implications for Korean companies and the government. While Korea possesses data collection technology and AI R&D capabilities, it needs a clear strategy and roadmap on how to integrate and apply these to climate change response. Of course, challenges associated with AI adoption also exist. A prime example is the relatively high cost of technology adoption, making it difficult for small and medium-sized enterprises (SMEs) to access. Furthermore, operating AI systems requires specialized personnel and infrastructure, and issues of data quality and security must also be addressed. However, experts commonly view AI technology as a crucial investment that, in the long term, simultaneously brings cost savings and efficiency, ultimately enhancing corporate competitiveness. Especially in a global supply chain where transparency of carbon emission information is increasingly becoming a critical competitive factor, AI-based carbon management systems are becoming a necessity, not an option. Future Climate Policy Drawn by AI We have now reached a point where specific discu