AI could soon consume billions of liters of water each year — much of it drinking water, says electrical and computer engineer Shaolei Ren. He dives into how energy-intensive training of large AI models, data center cooling and chip manufacturing all contribute to AI's massive “water footprint,” advocating for greater transparency, smarter resource management and more sustainable practices to reduce AI’s environmental impact, before it’s too late.