We’ve already seen trillions of dollars poured into solar panels, wind farms, battery storage, and grid upgrades under the banner of green energy. The narrative was seductive: build out renewables, clean tech wins, fossil fuels fade away. But that storyline underestimated what happens when energy demand explodes and it just did, thanks to AI, data centers, and electrification. Data centers and AI workloads are now among the fastest-growing power consumers in the world. Electricity demand from AI and server farms could double by 2030. In the U.S. alone, data centers are expected to consume more power than some major industrial sectors combined. The moment GPUs started training trillion-parameter models, every assumption about “flat power demand” went out the window. That’s where the weakness of renewables becomes obvious. Intermittent sources like solar and wind can’t reliably deliver baseload power, especially when demand spikes or when you need consistent, high-density energy around the clock. The “duck curve,” grid instability, and massive storage inefficiencies mean we would need to overbuild generation and storage capacity to absurd levels just to keep up. The result: even more capital waste or major reliability risk. So now we face a paradox. We’ve spent a decade betting on a clean-only future, yet the sharp rise in AI and digital energy demand requires scale and reliability that renewables alone can’t deliver. If we refuse to lean on fossil fuels, we risk ceding the energy foundation of the future to China, a country that burns coal unapologetically while building out the largest AI infrastructure in the world. Fossil fuels aren’t just coming back. They’re about to become the geopolitical lever of the decade. Oil, gas, and even coal offer dispatchable, scalable energy density that no battery can replicate. In a world where energy equals intelligence, whoever controls reliable power controls the AI frontier.