The US is cutting funding for the National Science Foundation (NSF), which finances scientific research programmes, pushing research into private labs, while European nations step public investment up. This signals where the next generation of talent and ideas may emerge from, crucial for those of us building companies at the frontier of artificial intelligence.

From university lab to disruptive startup

Pathway’s roots trace back to academia, as do those of DeepMind, Databricks, and many others. Universities are fertile ground for deeptech innovation, where research is driven by interest and a desire to solve problems as opposed to commercial value.

University researchers are often ahead of the market and discoveries are not restricted to those specifically researching AI. New ideas may be triggered by mathematicians, physicists, or neuroscientists and shaped into AI breakthroughs through the collaboration that academic settings enable. Stifling any area of science research could impact AI progress.

Is the US undermining its emerging startups?

The US’s academic community is a building block in its position in the AI race. However, slashed NSF funding means labs are making redundancies, cancelling grants, and scaling back research. This is a risk to academia and the wider tech ecosystem, manifesting as fewer ideas to commercialise and a drying talent pipeline as we lose educators over time.

This is not a purely short-term concern. If the US fails to invest in academic research infrastructure, it could face long-term expertise erosion, as seen in France’s nuclear sector after decades of underinvestment. Without academic leaders passing knowledge to upcoming researchers and scientists, the US could lose its leadership for AI skills.

Big tech’s growing grip

With receding public funding, private companies’ influence over AI research increases. Corporations have the resources to push boundaries, but their incentives are commercial.

Access to cutting-edge research becomes gated, talent is absorbed into corporate labs and independent innovation shrinks. This strengthens the biggest companies’ hold of the best resources and talent, making it harder for newer disruptors to develop their ideas. When smaller businesses suffer, so does the entire tech ecosystem.

Europe’s moment to lead

There is a clear contrast on the other side of the Atlantic. The European Union has invested €500 million into the ‘Choose Europe for Science’ initiative, and the UK, France, and Netherlands have launched national programmes. This signals a commitment to academics.

Researchers go where they can experiment freely and collaborate. More public research funding in Europe means more discoveries and early-stage investment opportunities. If the continent can pair financial commitments with practical support and competitive salaries, it will attract talent and become the launchpad for the next generation of AI startups.

The investment gap

Of course, ambition alone isn’t enough. Despite its pledges, Europe lags significantly behind the US in overall R&D spending. To truly compete, it will need to close this gap with an additional annual spend of €750-800 billion.

It must also address barriers to relocation. Simplified immigration policies, affordable housing and access to quality resources are essential for Europe to be a viable choice for researchers.

Startups and the future of academic research

Thirteen top universities including Massachusetts Institute of Technology (MIT) and Princeton University have filed a lawsuit to block the US’s funding cuts. However, if these efforts are unsuccessful, and Europe follows through on its vision, we may see a new centre of AI academia.

The regions that invest in talent and research will shape the technologies and companies of tomorrow and for startup founders and their investors, this is a crucial moment.