In the escalating race for artificial intelligence supremacy, a new resource has emerged as the most critical commodity: raw compute power. Once relegated to the backend of tech development, the physical hardware and computational resources required to train and run complex AI models—like GPUs and supercomputers—are now viewed as the “new oil,” a vital and increasingly scarce resource that nations and corporations are vying to control.
The parallel to crude oil is apt. Just as energy security has defined geopolitical strategy for decades, “compute security” is becoming a defining factor in the AI era. The development of cutting-edge AI, particularly large-scale generative models, is a profoundly compute-intensive endeavor. These systems, which can generate unprecedented amounts of new content, require massive data centers consuming megawatts of electricity and housing tens of thousands of specialized chips. Experts note that the amount of computation needed to train the most advanced AI models is growing by a factor of five each year, a trend that shows no sign of slowing.
This exponential demand has created a bottleneck in the AI supply chain. Companies like Nvidia, which dominates the market for AI chips, are struggling to meet the insatiable demand. This scarcity has created a fierce, high-stakes competition. Major tech companies such as Google, Microsoft, and Amazon are investing billions of dollars in building proprietary AI infrastructure. Meanwhile, nations are recognizing that access to compute is no longer just an economic advantage but a matter of national security and sovereignty. Governments, including those in Saudi Arabia and Japan, are allocating massive budgets to acquire and build their own AI compute capacity, reflecting a global understanding that future economic and military power will be intrinsically linked to AI capability.
The “bitter lesson” of AI history, as some researchers call it, reinforces this trend. Time and again, approaches that leverage sheer computational brute force and massive datasets have proven more effective than those based on complex, human-like reasoning. This makes the physical infrastructure—the chips, the servers, and the data centers—the true foundation of AI progress. As the world shifts from an information-based economy to one of creation and generation, the control of the “new oil” will determine who leads the next technological revolution.
