Trump policies are helping ensure the US leads in global AI revolution, White House economic advisers argue

The U.S. is sustaining its lead in the global artificial intelligence race, according to a new report published by the Trump administration, citing multiple economic indicators that could point to a widening global gap in AI-driven growth akin to the effects of the Industrial Revolution.

The report, published on Wednesday, was authored by the White House Council of Economic Advisers. Its key mission was to document the growing divide between wealthy, industrialized nations that can afford to invest in artificial intelligence and developing countries that are potentially lagging behind.

“The AI revolution, with its parallels to the Industrial Revolution, presents a profound economic inflection point with the potential to significantly increase the GDP of countries that embrace it,” the report reads. 

Citing economic research from 2000 on the Industrial Revolution and resulting Great Divergence — the era where the growth of countries that adopted new technologies outpaced countries which didn’t — the report notes that AI has the potential to bring about a similar global sea change. It hinges on several metrics that gauge how investment, innovation and adoption of AI technologies stand to impact the U.S. and other economies.

The first metric the report introduces is the economic concept of Total Factor Productivity, an indicator that gauges an economy’s efficient usage of inputs — such as labor and resources — to generate outputs — such as GDP. The report authors state that while this is an important metric that reveals AI’s impact on productivity, measuring investment in multiple AI domains, from the models themselves to their supporting infrastructure, is also key. Sustained investment despite rising costs “indicates a commitment to developing more capable and complex AI systems.”

Another metric of AI growth in the U.S., according to the report, is the performance of the systems themselves: their ability to execute increasingly complex tasks, the lowering cost per input for large language models, the widespread adoption by individuals and businesses and the self-projected revenue growth for companies like OpenAI, which “would be far higher than the growth rate seen by these previous big tech unicorns.”

The report also conducts a cross-country analysis to rank global players based on investment, performance, and adoption of AI, determining that the U.S. is in a clear lead. 

In investment, the U.S. lead is supported predominantly by the volume of private financial investment in AI, where other nations have made more direct state-backed or sovereign wealth investments, the report notes.

“The United States had $109 billion in private AI investment in 2024, compared with just $9 billion of private investment for second-place China, with the UK, Sweden, and Canada rounding out the top 5,” the report says. “Unsurprisingly then, the U.S. has about 75 percent of reported venture funding in generative AI startups.”

The U.S. also has the largest share of AI models exceeding 10^23 FLOPs of compute power — about the size of GPT-3 — representing 154 of the total 331 systems of that capability in the world as of 2024. The report notes, however, that “due to the rapid speed of AI advancement, the performance gap between the best models of each country is relatively small.”

Finally, as of May 2025, the U.S. was home to approximately 74% of the world’s AI compute capacity, per the report, and much of the hardware used to train AI models in other countries was made in America.

The report closes with touting the “Trump Revolution,” characterized by large-scale investments in AI and the administration's deregulatory efforts, as a means of improving U.S. performance in each of the indicators. The authors argue that investment-friendly provisions in the One Big Beautiful Bill Act and trade agreements facilitated by this administration will further boost U.S. AI investment. The authors also link administration imperatives around energy dominance to improving adoption and usage of notoriously energy-hungry AI systems.

“The United States, as demonstrated by the comprehensive AI Action Plan and related executive orders from the Trump administration, is pursuing a strategy focused on accelerated innovation, infrastructure development, and establishing global dominance through technology exports and deregulation in order to lay the groundwork for American AI dominance,” the report concludes. 

Susan Aaronson, a research professor of international affairs at George Washington University and the director of its Digital Trade and Data Governance Hub, said leveraging AI in existing economic arenas, such as manufacturing, comes with both positives and negatives that demand policymaker attention.

“When we think about AI, we need to also imagine how AI might be utilized to bolster existing economic sectors and create new sectors,” she told Nextgov/FCW. “However, policymakers have not yet reckoned with how these technologies may alter the global economy or lead to manufacturing overcapacity. It could, as [an] example, lead to fewer manufacturing jobs and real stress on trade, social security, fiscal and monetary policies as well as social stability.”

Tara Sinclair, an economist at George Washington University, spoke to economists’ desire to look to patterns in history for forecasting AI at a December Brookings Institute virtual event. Like Aaronson, Sinclair said that AI can bring good and bad into economic sectors, but notes it will take time, closer to 20 or 30 years to be really transformative. 

“People keep focusing on how fast AI can scale, and, at the same time, we have to think about [the fact that] humans take a lot more time, and we’re going to have to create new businesses, new firms, in order to really adopt this technology,” she said.

Editor's note: This article has been updated to include comment from Tara Sinclair.