Can AI Help Solve Sustainability Challenges?

Main points — free preview

• AI can accelerate climate modeling, biodiversity monitoring, and materials discovery — but training and deploying large models consumes significant energy, complicating the net environmental calculus.
• Earth system models and ML-enhanced weather prediction have produced measurable improvements in forecast accuracy and resolution — applications where AI's energy cost is justified by downstream climate adaptation benefits.
• Greenwashing risk is real: not every AI product marketed as 'sustainable' reduces emissions. Credible environmental AI requires published benchmarks, lifecycle accounting, and domain-specific validation.