The AI race in biotech: Is Europe falling behind the US and China?

Since the blockbuster release of OpenAI’s ChatGPT in 2022, artificial intelligence (AI) seems to have found its way into every industry, not least the biotech sector, where it has been adopted by numerous companies in the last few years to help with a varying degree of tasks, namely in the drug development process. However, not every major biotech region has taken AI on board with such vigour; these companies are primarily based in the U.S. and China, whereas Europe has significantly lagged behind in its adoption of AI. 

But why exactly has Europe fallen behind in the AI race? That is what we will be exploring in this article. 

European biotech lags behind in AI, as the US and China lead the way

In October 2024, Jensen Huang, the CEO of AI chipmaker Nvidia, commented that the European Union (EU) lags far behind the U.S. and China when it comes to investing in AI. Not long after, French President Emmanuel Macron also told CNN in an exclusive interview that Europe is lagging behind, stating that the bloc is simply “not in the race today.” 

Indeed, the U.S. and China are currently miles ahead in their adoption of AI. The U.S., in particular, has a commanding lead in AI technology, according to a recent report from Stanford University. In 2023, the U.S. Food and Drug Administration (FDA) approved 223 AI-enabled medical devices, up from just six in 2015. In 2024, U.S. private AI investment grew to $109.1 billion (nearly 12 times China’s $9.3 billion). 

Additionally, U.S.-based institutions produced 40 notable AI models in 2024, significantly outpacing China’s 15. However, while the U.S. maintains its lead in quantity, Chinese models have rapidly closed the quality gap, and China continues to lead in AI publications and patents.

Europe, on the other hand, is scarcely mentioned in Stanford’s report. And, when it is mentioned, the figures do not look good: European institutions only produced three notable AI models – all of which were French. 

In a separate 2024 report, Stanford also found that no EU country made the top five for “vibrancy” in AI, a metric that considered private investment, patents, and research. The U.S. and China ranked first and second, respectively, with France in sixth place and Germany in eighth. It’s also worth noting that the U.K. actually ranked third on the list, which, although no longer in the EU, is of course part of Europe geographically, and appears to have a more vibrant AI startup scene. 

“A common perception exists that the U.S. holds an advantage over Europe in AI innovation and getting drugs to market more quickly, specifically in the areas of investment and funding, and digital infrastructure,” commented Cem Zorlular, chief executive officer (CEO) of Er-Kim Pharmaceuticals. “In addition, complex EU regulations on the use of AI can slow down AI-driven solutions in the biotech space, resulting in Europe seeming to ‘lag’ other regions.”

The main barriers to AI adoption for Europe’s biotech industry

Indeed, there are a few different factors that have contributed to Europe falling behind in the biotech AI race. Here, with the help of Zorlular and Natalie Dolphin, managing director of Investor Relations at HLTH Communications, we detail the main factors.  

Regulatory and ethical constraints 

Both Zorlular and Dolphin agree that the EU’s regulatory constraints on AI have played a role in the region’s lag in adopting the technology. “The EU’s stricter data protection laws (GDPR) and evolving AI-specific regulations mean companies must navigate a more intricate compliance framework than in the U.S. or China,” said Dolphin.

In 2024, the EU passed the EU AI Act, the world’s first comprehensive regulation on AI, in an effort to ensure better conditions for the development and use of the technology. Essentially, the priority in enforcing this law is to make sure that AI systems used in the EU are safe, transparent, traceable, non-discriminatory, and environmentally friendly. AI systems should be overseen by people, rather than by automation, to prevent harmful outcomes.

The Act works by assigning applications of AI to three risk categories. First, applications and systems that create an unacceptable risk, such as government-run social scoring of the type used in China, are banned. Second, high-risk applications, such as a CV-scanning tool that ranks job applicants, are subject to specific legal requirements. And, lastly, applications not explicitly banned or listed as high-risk are largely left unregulated.

Of course, this focus on data security and ethical AI use is important, but it also plays a big part in slowing down AI integration in biotech and other industries in the region. 

“With more strict requirements in place for transparency, data governance, human oversight, and accuracy, the EU biotech industry may find it especially difficult to handle the high compliance costs that stricter guidelines impose, potentially hampering biotech innovation in Europe,” said Zorlular.

Investment trends and challenges 

The investment landscape in Europe is another key reason for AI struggling to get off the ground in the same way as it has in the U.S. and China. 

“European biotech funding tends to be more conservative, with a lower risk appetite compared to the U.S., where AI-driven biotech startups often receive large-scale funding,” explained Dolphin. “The challenge isn’t a lack of innovation – European research institutions are world-class – but rather a gap in turning that innovation into commercially viable AI-driven solutions. Bridging this gap requires not just more capital but also a shift in investment mindset toward high-risk, high-reward AI ventures.”

Zorlular concurred with this, saying the U.S. has a much larger and more mature venture capital ecosystem, especially for high-risk, high-reward investments like AI. “While U.S. biotechs have access to greater funding for research, development, and commercialization, Europe faces challenges in attracting the same level of investment,” he commented. 

Issues with academic and industry collaboration 

Dolphin also explained that, although Europe’s strength in AI and biotech research is undeniable, there is a disconnect between academic advancements and industry application, whereby many promising AI innovations remain stuck in research labs, failing to make their way into startups or established biotech firms to be developed further. 

When looking at what actually drives this disconnect within academic and industry collaborations, Dolphin said that several factors are at play. “One key issue is the lack of structured pathways for translating research into commercial biotech ventures. Academic institutions often prioritize publications and theoretical advancements over commercialization, and researchers may not have the resources or entrepreneurial support needed to spin out companies.”

There is also the fact that industry and academia can sometimes operate in silos, with limited communication or alignment on objectives, which can ultimately lead to promising technologies being underdeveloped or misunderstood by potential commercial partners. Additionally, academic institutions in Europe can be more risk-averse when it comes to intellectual property (IP) licensing or early-stage startup involvement compared to their counterparts in the U.S.

“To improve this bottleneck, stronger public-private partnerships and clearer incentives for academics to engage with industry would help,” commented Dolphin. “Dedicated translational funding, mentorship programs, and biotech accelerators that actively bridge academia and industry could also facilitate more successful commercialization efforts. American institutions have figured out how to do this, and Europe is not far behind.”

In turn, this could allow for more AI technology to actually make its way out of research labs and into the hands of biotech startups with the capability to develop it further. 

Recent progress: EU shows willingness to play catch-up with AI gigafactories announcement

But not all is doom and gloom for Europe, as it seems like the region is taking Macron’s pleas on board by recently announcing the details of a €20 billion ($23 billion) plan to build AI gigafactories in an attempt to catch up with the U.S. and China. 

The EU has already embarked on a plan to build 13 AI factories, but these gigafactories would be much larger, targeting what the European Commission called “moonshots” – in other words, significant innovations in healthcare, biotech, industry, robotics, and scientific discovery.

This comes under a strategy to turn Europe into an “AI continent” and involves the creation of new sites in Europe equipped with vast supercomputers to develop the next generation of AI models, while potentially simplifying the EU AI Act as part of a wider drive to cut red tape amid concerns about Europe’s lagging economic growth.

The European Commission vice-president Henna Virkkunen said the technology was at the heart of making Europe more competitive, secure, and technologically sovereign. As she put it: “The global race for AI is far from over.”

It is true that, with AI still in its early stages and much of its productivity gains yet to be unlocked, the window of opportunity for Europe to catch up to the U.S. and China in the AI race remains wide open.

According to Dolphin, there are four key priorities that Europe can do to catch up when it comes specifically to AI in biotech. These are: 

• Increased government incentives: AI-focused biotech funding programs and grants could help de-risk early-stage ventures.
• Streamlining regulations: Establishing clearer, AI-specific regulatory pathways in healthcare and biotech would enable faster adoption.
• Encouraging cross-border collaborations: Partnerships with AI-driven biotech leaders in the U.S. and Asia could bring expertise, funding, and market access.
• Strengthening AI infrastructure: More support for biotech incubators and accelerators focused on AI applications would create an environment where startups can thrive.

Ultimately, the rewards of catching up to the U.S. and China could drastically benefit the EU; according to McKinsey & Company, generative AI could add $575.1 billion to the European economy by 2030. 

“Europe has all the ingredients to be a leader in AI-driven biotech – cutting-edge research, strong regulatory frameworks, and a robust biotech sector,” stressed Dolphin. “What’s needed now is a more aggressive push toward investment, regulatory clarity, and industry collaboration to ensure AI’s full potential is realized in biotech.”