If the United States is serious about leading the world in artificial intelligence, it must confront a difficult truth: AI is not just about algorithms, venture funding, cloud platforms, or research labs. It is about energy and power grids, natural resources and supply chains, and human capital.
Right now, the U.S. is unprepared for what is coming. China is rapidly integrating energy expansion, data center capacity, human capital, and global AI exports into a coherent national strategy.
The U.S. currently lacks the dependable, affordable, and scalable power needed for sustained AI development, a recent study by the American Edge Project showed. China, by contrast, has aggressively invested in energy and transmission for years, and as a result, is producing twice as much electricity as the U.S.
WHY BREAKING CHINA’S GRIP ON CRITICAL MINERALS CAN’T WAIT
Contrary to common belief, the data centers that power AI aren’t the cause of the energy challenge we face — they merely expose three decades of underinvestment in America’s transmission grid.
Closing that gap requires an all-of-the-above approach to power generation — nuclear, natural gas, renewables, and advanced energy sources. We must onshore critical supply chains by incentivizing domestic production of gas turbines and power transformers to eliminate multiyear wait times. And we must modernize and secure the grid by streamlining permitting, expanding transmission, and protecting infrastructure against cyber threats. Utilities, regulators, developers, and communities must come together to fast-track the power projects critical to America’s AI future.
Supply chains are equally vulnerable. Every layer of AI infrastructure, from chips to networking switches to heat exchangers, depends on global supply chains that the U.S. does not fully control. More than 90% of the world’s most advanced semiconductors are produced in Taiwan, leaving us exposed to supply disruptions, political upheaval, or economic coercion. Rare earth processing remains overwhelmingly concentrated in China. JP Morgan’s recent $1.5 trillion commitment toward critical minerals underscores how seriously markets are taking these vulnerabilities — and so must we.
Continued investment in semiconductor manufacturing and AI accelerator development is essential to maintaining the U.S.’s compute advantage. We must secure critical mineral supply chains by developing domestic rare earth processing and diversifying sources beyond China’s chokehold. And we must prevent harmful regulation by enacting a multiyear freeze on state AI laws, rejecting restrictive copyright theories, and resisting antitrust experiments that would weaken U.S. innovators.
The AI race is ultimately a talent race. The U.S. does not have enough of the skilled workforce needed to build and maintain rapid expansions of AI infrastructure. Semiconductor technicians, materials scientists, AI systems engineers, and specialized tradespeople are in short supply or aging out of the workforce. Replacements are not emerging fast enough. Meanwhile, China is producing engineers at nearly quadruple the U.S. rate — a deficit we cannot afford to ignore.
Making AI workforce development a shared national initiative across government, industry, and education must be an urgent priority. That means AI and computer science requirements in middle and high schools, expanded STEM investments, and workforce retraining programs for AI-adjacent fields. It also means streamlining H-1B visas and creating new pathways for AI talent from allied nations.
None of this is abstract. The promise of AI is a pathway to higher wages, lower costs, and more upward mobility for millions of families. But that promise evaporates if we fail to deploy. China understands this and is rapidly embedding AI across its industrial base, civil services, and foreign partnerships.
U.S. adoption remains fragmented and slowed by uncertainty and regulatory confusion.
CHINA’S MINERAL MONOPOLY IS PUTTING OUR NATIONAL SECURITY AT RISK
We must move faster, both at home and abroad. That means building public trust through demonstrated benefits, promoting AI literacy, and exporting an American AI stack that carries with it the values of openness, opportunity, and transparency. It means giving allies priority access to U.S. chips, models, and cloud infrastructure while leading the world in setting democratic AI governance standards.
AI leadership is global leadership; It is energy leadership, supply chain leadership, and workforce leadership. The window to build it is open now. It will not stay open forever.
Kent Kaiser, Ph.D., is the executive director of the Trade Alliance to Promote Prosperity. Doug Kelly is the CEO of the American Edge Project, a nonprofit coalition dedicated to strengthening the U.S.’s technological leadership.