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Why the EU’s AI talent strategy needs a reality check 

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A raft of recent policy changes in the U.S. touching trade, immigration, education, and public spending has sparked upheaval in research communities around the globe. The American economy, once the dream destination for the most talented, suddenly looks like it could lose its allure for the world’s brightest scholars. The sudden crisis of faith in the American innovation ecosystem has also sparked a fresh debate: Can the European Union seize the moment to attract disenchanted researchers and strengthen its own innovation ecosystem? 

The opportunity is real for Brussels, and the stakes are high, as the EU continues to trail the U.S. on virtually every cutting-edge technology—including artificial intelligence. A recent BCG Henderson Institute report shows that that stricter immigration rules and deep funding cuts for academic research in the U.S. raise the possibility that top AI researchers, a large share of whom are not U.S.-born, could look to take their talents elsewhere. Repatriating those top European academics is an important step for European policymakers, but to catch up, the EU must also be able to attract talent beyond the European diaspora, which is only a small fraction of the globally mobile AI talent base.

To remake itself into a tech talent magnet, Europe needs to build an academic ecosystem more closely integrated with its industries, a necessary step to provide the career pathways and information flows needed to turn academic discoveries and inventions into business value. The cost of this transformation will be considerable, as publicly discussed in, for instance, the Draghi report. Only then can the EU’s investments in academia help generate longstanding economic and geopolitical returns for the bloc.

The opportunity for Europe must not be overstated 

The EU recently announced a €500 million allocation over the next two years to help attract foreign researchers. Member states have also launched their own initiatives, including France’s €100 million commitment to its “Choose France for Science” platform to attract international researchers, and Spain’s €45 million pledge to help lure scientists “despised or undervalued by the Trump administration.” 

If these investments are made with the sole aim of repatriating European AI talent in the U.S., they risk falling short. The U.S. is home to roughly 60% of the top 2,000 AI researchers in the world, only one-fifth of whom are originally from continental Europe. Even an exodus of historical proportions would cover only half of the current gap between the EU and U.S. shares of the top AI researchers. 

At top GenAI labs, such as OpenAI and Anthropic, only a very small fraction of AI specialists (less than 1 percentage point of the 25% of workers who have completed their undergraduate degree outside of the U.S.) completed their bachelor’s degree in the EU. The future pipeline of AI talent is no different: In 2023, the top 10 contributing countries of foreign-born PhD recipients in computer science and mathematics to the U.S. accounted for 80% of the total. But not one of those countries is in continental Europe.

The U.S. AI research ecosystem is overwhelmingly supported by talent from Asia, not Europe: 85% of U.S.-based foreign nationals in technical AI jobs at leading American labs hail from China or India. So do 60% of all U.S. computer science and math Ph.D graduates in the U.S. Iran, Bangladesh and Taiwan account for most of the rest. If the EU is serious about becoming a vibrant hub for global AI research talent, it needs to look eastward.

But current (and prospective) AI researchers often don’t see Europe as a top destination. BCG’s Talent Tracker shows that Germany does best among European countries, ranking 5th globally as a “dream destination” for highly skilled talent, followed by France (9th), Spain (10th), and the Netherlands (16th). The EU is not just less attractive than the U.S. (2nd), but also Canada (3rd), the UK (4th), and Australia (1st), and roughly on par with the UAE (11th). European countries are by no means the only nations committed to boosting their own talent bases.

Part of the challenge is the lack of large EU academic institutions with strong AI credentials compared to other regions. None of the top 50 AI institutions worldwide (as ranked by Google Scholar’s H5 journal impact index) are in the EU. A strong institutional base for leading AI labs is essential to create the work environment capable of attracting the best and brightest. 

The EU needs to invest in its universities to improve its standing, but it must also look beyond academia to improve its entire innovation ecosystem. Nearly a third of non-U.S. AI specialists go to the U.S. because of its extensive opportunities for career growth, including entrepreneurial endeavors, a BHI survey of top tech talent recruiters found.

The need for a concerted strategy across academia and industry

To get started, European countries must improve academic compensation in critical fields related to AI, and technology more broadly. In Europe, even when adjusting for purchasing power parity, salaries at the associate professor level are half of those paid at top U.S. institutions. Europe also needs to increase grant availability for research. Public research grants for computer science and informatics at leading American AI institutions are double those available in Europe. Europe may get a boost however, if the U.S. goes through with proposed cuts to the National Science Foundation’s budget.

It’s well known that incentives for innovation matter. In the 2000s, a few European countries reformed their academic patenting laws to follow the U.S. model, where American universities hold patent rights and share commercialization profits with professors. But the reforms were not well tailored to the European context and led to a significant decrease in academic patenting (between 17% and 50% depending on the country).  

Furthermore, only about a third of patented inventions from EU universities and research institutions ever get exploited, largely due to their weak integration into innovation clusters that drive commercialization. Even the best EU innovation clusters, once again, fall outside the top 10 globally, with the U.S. accounting for four spots, and China three. To change that, it’s essential for European policymakers to help build stronger bridges between academia and industry to ensure that foundational research effectively fuels economic value creation.

That includes strengthening the startup and innovation ecosystem around universities themselves. The ultimate aim of attracting top AI researchers is not to simply catch up, but to skip ahead and produce the next IP breakthrough, which will only rise in importance as more AI models become commoditized. Coming up with the next big thing, however, requires an investment environment capable of supporting ambitious bets on potential breakthroughs coming out of academia. Countries like Canada and the U.K. serve as cautionary tales of AI research hotspots that have often struggled to translate academic breakthroughs into commercial successes, a leap successfully undertaken by large U.S. tech companies.

Many of the usual items in the European reform menu will also bolster the AI talent and innovation ecosystem. As the 2024 Draghi report on the future of European competitiveness noted, the integration of EU capital markets is vital, as is the removal of internal trade barriers that hamper early-stage startups’ growth. Between 2019 and 2024, AI venture capital investment in the EU was just a tenth of that in the U.S. It is no wonder then that nearly a third of European “unicorns” founded between 2008 and 2021 relocated elsewhere—usually to the U.S. 

But crucially, the list of reforms must also include strong incentives for AI adoption. At present, EU companies lag their U.S. counterparts in generative AI adoption by between 45% and 70%. Closing that gap will simultaneously help fuel European demand for specialized AI talent and create the economic opportunities beyond academia that are critical to attracting the world’s best and brightest.

Overconfidence could set back the EU 

The EU is right to want to lure researchers into its academic institutions that have historically pushed the frontier of AI. This will require revamping the academic ecosystem and more systematically translating academic breakthroughs into long-term economic and strategic leadership. 

But it would be wrong for European policymakers to assume that the erosion of U.S. attractiveness will organically lead to a talent windfall, predicated on their belief that Europe is the inevitable “next best” option. That will only be true if the region acts decisively to build its own, integrated, AI ecosystem capable of attracting the brightest minds from China, India, and beyond. In the AI race, as on many other fronts, the EU bears the risk of being too confident in its belief that it is entrenched in third place. That kind of complacency could very well accelerate the EU’s descent into the minor leagues of global innovation.

***

Read other Fortune columns by François Candelon.

François Candelon is a partner at private equity firm Seven2 and the former global director of the BCG Henderson Institute

Etienne Cavin is a consultant at Boston Consulting Group and a former ambassador at the BCG Henderson Institute.

David Zuluaga Martínez is senior director at Boston Consulting Group’s Henderson Institute.

Some of the companies mentioned in this column are past or present clients of the authors’ employers.



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xAI lays off 500 AI tutors working on Grok

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Elon Musk’s artificial intelligence startup xAI has laid off 500 workers from its data annotation team, which helps train its Grok chatbot.

The layoffs were earlier reported by Business Insider.

The AI company notified employees over email that it was planning to downsize its team of generalist AI tutors, according to messages viewed by the publication. The company said the “strategic pivot” meant prioritizing specialist AI tutors, while scaling back its focus on general AI tutor roles.

In response to the story, xAI directed reporters to a post on X, in which the company said it plans to expand its specialist AI tutor team by “10X” and intends to open roles on its careers page.

The human data annotator team at xAI plays a key role in teaching Grok to understand the world by labeling, contextualizing, and categorizing raw data used to train the chatbot. The email sent by xAI said that laid-off workers would be paid through either the end of their contract or Nov. 30, but their access to company systems would be terminated the day of the layoff notice.

Prior to the layoff, the xAI’s data annotation team was one of the largest, with 1,500 full-time and contract staff members, which included AI tutors. The reorganization of the data annotators team comes on the back of a leadership shake-up at the team that saw nine employees reportedly exit the firm last week.

As a sign of its changing approach to training Grok, xAI on Thursday asked some of the AI tutors to prepare for tests, Business Insider reported, that covered traditional domains such as STEM, coding, finance, and medicine, as well as quirkier specialties such as Grok’s “personality and model behavior” and doomscrollers.”

Musk launched xAI in 2023 to compete with OpenAI and Google DeepMind, which are racing to win the AI race. He introduced Grok as a safe and truthful alternative to what he accused competitors of building, “woke” chatbots prone to censorship.



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Google’s newest AI datacenter & its monstrous CO2 emissions

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The impact of the rise of AI on the environment is a very real concern, and it’s not one that’s going away in a hurry. Especially not when Google’s planned new datacenter in the UK looks set to emit the same quantity of Carbon Dioxide in a year as hundreds of flights every week would.

It comes via a report from The Guardian, which has seen the plans for the new facility and the very real carbon impact assessment.



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China doubts artificial intelligence use in submarines

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by Alimat Aliyeva

The integration of artificial intelligence into submarine
warfare may reduce the chances of crew survival by up to 5%,
according to a new report by the South China Morning Post (SCMP),
citing a study led by Meng Hao, a senior engineer at the Chinese
Institute of Helicopter Research and Development,
Azernews reports.

Researchers analyzed an advanced anti-submarine warfare (ASW)
system enhanced by AI, which is designed to detect and track even
the most stealthy submarines. The system relies on real-time
intelligent decision-making, allowing it to respond rapidly and
adaptively to underwater threats. According to the study, only one
out of twenty submarines may be able to avoid detection and attack
under such conditions — a major shift in naval combat dynamics.

“As global powers accelerate the militarization of AI, this
study suggests the era of ‘invisible’ submarines — long considered
the backbone of strategic deterrence — may be drawing to a close,”
SCMP notes.

Historically, stealth has been a submarine’s most valuable
asset, allowing them to operate undetected and deter adversaries
through uncertainty. However, the rise of AI-enabled systems
threatens to upend this balance by minimizing human response
delays, analyzing massive data sets, and predicting submarine
behavior with unprecedented precision.

The implications extend far beyond underwater warfare. In
August, Nick Wakeman, editor-in-chief of Defense One, reported that
the U.S. Army is also exploring AI for use in air operations
control systems. AI could enhance resilience to electronic warfare,
enable better integration of drones, and support the deployment of
autonomous combat platforms in contested airspace.

The growing role of AI in modern militaries — from the seabed to
the stratosphere — raises new questions not only about tactical
advantage, but also about ethical decision-making, autonomous
weapons control, and the future of human involvement in combat
scenarios.

As nations continue investing in next-generation warfare
technology, experts warn that AI may not just change how wars are
fought — it could redefine what survivability means on the modern
battlefield.



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