The future of AI competitiveness hinges on access to cheap, reliable electricity, not just superior models or user experiences. Data centers' substantial electricity consumption is driving up prices, shifting the constraint from GPUs to kilowatt-hours. Concerns about water usage in AI are often exaggerated; most cooling systems recirculate water, with only evaporative cooling consuming significant amounts. Water stress is a localized issue, dependent on location and cooling technology. Cheap, clean energy sources like wind and solar are significantly cheaper than alternatives like nuclear or gas. China's rapid expansion of renewable energy gives it a considerable advantage in low-cost electricity production. The US needs to prioritize building cheap renewable energy infrastructure to remain competitive in AI. Companies should prioritize regions with abundant renewable energy and negotiate favorable energy pricing. Focusing on efficient cooling designs and sustainable energy sources is crucial for cost control and responsible AI development. Ultimately, access to inexpensive, consistent electricity will determine the winners in the AI race.