Can AI help achieve green and low-carbon goals?

AI can significantly advance green and low-carbon goals by optimizing energy use and reducing emissions. Its ability to analyze complex data makes it a crucial tool in the sustainability transition.

AI enables smarter resource management and environmental monitoring, requiring access to accurate data. Key applications include predicting and balancing renewable energy integration into grids, optimizing industrial processes and logistics for energy efficiency, and detecting emissions. Accuracy depends on robust data inputs, model quality, and computational efficiency. Its effectiveness spans energy, manufacturing, agriculture, and transportation sectors. However, the environmental footprint of AI computation itself must be managed.

AI drives low-carbon progress through predictive maintenance reducing waste, precision agriculture conserving resources, and advanced climate modeling guiding mitigation. Optimizing building energy use and developing sustainable materials further demonstrate its value. Ultimately, AI offers crucial capabilities for measuring progress, identifying efficiency gains, accelerating innovation, and enabling the large-scale systems changes needed to achieve net-zero targets.