OpenAI’s ChatGPT, the Nobel Prize-winning AlphaFold and advances in autonomous driving are just some of America’s A.I. breakthroughs made possible with federally-funded scientific research—funding that is now being slashed by Trump administration. As these resources disappear, scientists warn the U.S. risks a brain drain, diminished global influence in the field and forfeiting the long-term economic gains tied to technological innovation.
“It’s really like the U.S. has decided to cede our leadership in this area,” Nancy Amato, director of the University of Illinois Urbana-Champaign’s Siebel School of Computing and Data Science, told Observer. “I think it’s really going to be harmful to the country in the long term.”
The Trump administration’s onslaught of funding cuts is already rippling through academia. Several universities have paused Ph.D. admissions, reduced graduate enrollment or frozen staff hiring in recent months. While Amato’s department at the University of Illinois Urbana-Champaign has not cut its graduate offers this year, she noted that other institutions have warned incoming Ph.D. candidates they may not be able to provide standard funding packages.
The impact isn’t limited to graduate programs. Undergraduate summer research initiatives—designed to spark interest in advanced study by offering hands-on experience—are also at risk. Many of these programs target students whose high school years were already upended by the Covid-19 pandemic, Amato pointed out. “Now they’re undergrads and we’re again kind of saying, ‘Hey, sorry you can’t do this thing that we always had for everyone.’”
The consequences of diminished federal support go far beyond fewer research projects, according to Rebecca Willett, faculty director of A.I. at the University of Chicago’s Data Science Institute. “We’re not just losing opportunities for innovation—we’re losing the ability to train the next generation of researchers,” she told Observer. “We have a real risk here that we’ll end up with a lost generation of talent.”
America faces a brain drain
As funding dwindles, researchers worry that America’s ability to attract top talent will diminish. Some researchers are already looking elsewhere. In a recent Nature survey of 1,650 U.S.-based scientists, about 75 percent said they were considering relocating due to Trump-era disruptions, with many citing Europe or Canada as preferred destinations. The sentiment is even stronger among early-career scientists, nearly 80 percent of whom reported thinking seriously about moving abroad.
The U.S. has historically been a net importer of A.I. talent over the past 15 years, but that trend has reversed. In 2025, the U.S. began exporting talent, according to a recent report from data intelligence company Zeki Data.
International students, long drawn to the U.S. for research opportunities, may now start looking elsewhere as science budgets shrink and anti-immigrant rhetoric intensifies. “We have been the magnet for the best minds all over the world to come here,” said Amato. “If we lose that, it’s going to be really tough—that is something that I think will cause long-term damage that’s really hard to restore.”
Even domestic students are increasingly exploring options abroad. The University of Toronto reported a “meaningful increase in applications over previous recent years” from American students for the 2025–2026 academic year, according to a statement provided to Observer.
Sensing an opportunity, international institutions are stepping in to recruit American-based researchers. Earlier this month, the European Union and France unveiled a joint incentive package exceeding $560 million to attract U.S. scientists with fully funded research opportunities. In April, France also launched a separate initiative to support proposals from international researchers.
The prospect of losing both international and domestic talent represents a “huge threat,” said Hank Hoffman, Liew Family Chair for the University of Chicago’s computer science department. “We not only lose the ability to attract people from elsewhere, but we lose the ability to retain homegrown talent,” he told Observer.
Funding cuts undermine A.I.’s foundation
Though the Trump administration claims it wants to supercharge A.I. in the U.S., its policies may undermine the industry’s foundation. Many of the country’s most consequential breakthroughs—such as transformer architecture and diffusion models—originated in academia. Leading A.I. firms like OpenAI and Google continue to depend on a robust academic pipeline to supply their future researchers and engineers.
“Without research in academia, there would not be OpenAI, there wouldn’t be any of the technological breakthroughs we have today—that’s for sure,” Ruslan Salakhutdinov, a computer science professor at Carnegie Mellon University, told Observer.
In addition to freezing university funding, recent federal cost-cutting measures have also led to staff reductions and grant cancellations at key agencies like the National Science Foundation (NSF) and National Institutes of Health (NIH). These cuts could carry devastating long-term economic consequences. On the cautious side, a 25 percent reduction in public research and development spending would shrink the U.S. GDP by 3.8 percent, a decline comparable to that of the Great Recession, according to a recent study from American University. A 50 or 75 percent cut would result in GDP declines of 7.5 and 11.3 percent, respectively.
While A.I. research enjoys some insulation through industry funding, government support remains critical for launching high-risk, curiosity-driven projects. Initiatives like the Defense Advanced Research Projects Agency’s (DARPA) Grand Challenge, which jump-started the autonomous vehicle field two decades ago, would not have happened without federal backing. “Industry funding is great because it kind of fills in the gaps, but it’s not the ultimate thing for us because industry will only fund certain things that they see the value in,” said Salakhutdinov.
Because A.I. research frequently overlaps with other disciplines, cuts in adjacent areas will have a cascading effect. For instance, a lot of the foundational work behind A.I.-powered weather prediction tools depended on data from the National Oceanic and Atmospheric Administration (NOAA), which now faces budgetary threats. AlphaFold, the Google DeepMind A.I. system that transformed protein structure prediction, would not have been possible without the Protein Data Bank, a database built on research from NIH-funded biology labs.
“These funding cuts are going to not only have a direct impact on labs doing A.I. research and developing the next generation tools, but they’re also going to have indirect impacts by impacting the labs that are collecting these rich sources of data we use to train our models,” said Willett.
As the walls begin to close in around the U.S.’s lead in A.I. competitiveness, scientists are sounding the alarm. “Falling behind in an area that is important intellectually, economically and strategically is really dangerous,” said Hoffman. “All three of those areas are pretty important and I think the risk of losing leadership in any of them is pretty dramatic.”
