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AI’s Role in Climate Resilience: Bridging Technology and Sustainability

Published: December 4, 2024 by Kate Brow, The Climate Trust/Project Analyst

Digital technology is transforming conservation efforts and corporate sustainability—helping to address complex challenges and guide informed decision-making at scale. Artificial Intelligence (AI) is emerging as one of the most powerful assets in this toolkit, offering new and innovative ways to collect and analyze vast amounts of data in real time. However, as we strive to unlock the potential of AI, it is critical to understand its strengths and limitations to ensure that its use aligns with global sustainability goals.

For decades, environmental professionals have employed machine learning to classify land cover, track endangered species, and model climate change scenarios (1). As AI continues to evolve, its applications have expanded significantly, supporting efforts in climate resilience, carbon accounting, and developing nature-based solutions. As global warming reaches critical levels, AI has the potential to accelerate efforts to reduce greenhouse gas emissions. For instance, AI programs can quickly and accurately analyze intricate global value chains to calculate corporations’ Scope 3 emissions—tasks previously requiring extensive resources and expertise.

Today, corporate GHG accounting professionals leverage AI to track and reduce emissions, optimize energy efficiency, streamline operations, and monitor potential carbon credit investments (2, 3). AI can analyze data at a scale traditional fieldwork cannot achieve, making it possible to improve the design and monitoring of carbon projects. This reduces errors, inconsistencies, and fraud, ensuring carbon credits represent real emissions reductions (3).

The Climate Trust (TCT) utilizes AI technologies to assist in project development and management. In forestry, deep learning models can be trained to generate land use classification and fire damage assessments, supporting the accurate delineation of project boundaries. Recently, TCT completed the first approved drone-based rangeland health assessment for a grasslands project, utilizing drone collected imagery to track several important metrics of rangeland health. The use of AI to conduct these tasks eliminates assessor bias and supports repeatable data collection and analysis.

AI offers significant opportunities to advance conservation and sustainability, but its environmental impact must not be ignored. AI systems often run continuously in data centers that consume vast amounts of electricity. Frequently powered by fossil fuels, the high energy demands of AI contribute to increased greenhouse gas emissions (4). According to the International Energy Agency’s 2024 report, electricity consumption from data centers powering AI and cryptocurrency could account for 4% of global energy use by 2026—roughly equivalent to the entire electricity consumption of Japan (5). The environmental footprint of AI extends beyond its energy consumption; production, maintenance, and disposal of AI hardware results in increased water usage, electronic waste (e-waste), and pollution from transport and mining practices (4).

In recognition of the growing influence of AI, the COP29 Presidency launched the inaugural Digitalization Day on November 16th, 2024. More than 90 governments and over 1,000 members of the digital tech community endorsed the COP29 Declaration on Green Digital Action (6). The Declaration calls for digital tools to reduce GHG emissions, strengthen climate resilience, and advance sustainable development. The Declaration emphasizes the importance of mitigating the negative impacts of digital technologies, urging the digital industry to take responsibility for its environmental footprint (7).

Despite these challenges, there is agreement among scientists, professionals, and global leaders about the transformative potential of AI in sustainable development, GHG accounting, and climate change mitigation. AI presents an opportunity to increase the transparency and ease of GHG accounting and bolster the integrity of the carbon markets. As with any powerful tool, relying on AI alone can overshadow the societal changes necessary to reach climate action goals. We must prioritize sustainable practices, human oversight, and interdisciplinary collaboration in AI development to ensure we can harness its full potential to combat climate change while minimizing its potential costs to society.