The Talent Domain: Addressing Workforce Challenges in the EU's AI Continent Action Plan

The European Commission's AI Continent Action Plan, unveiled today, represents a significant effort to position Europe as a global leader in AI development and deployment. However, despite recognizing talent as a central pillar, the plan inadequately addresses what our research identifies as the most significant challenges to AI development: attracting, promoting, and retaining top AI talent. 

Our research into global AI talent ecosystems reveals that Europe's vision for AI dominance is built on unstable ground. While the Commission's plan acknowledges the importance of "reinforcing AI skills and talent across Europe," its approach to talent mobility and development appears limited. The plan's references to "facilitating legal migration pathways for highly skilled workers" and "incentivizing the return of European AI talent to the EU" suggest an incomplete understanding of talent dynamics in a global marketplace. 

More precisely, it overlooks three critical gaps that threaten to undermine Europe's AI aspirations, regardless of how much computing infrastructure it builds. 

A narrow definition of "high-skilled" talent

First, the plan operates with an outdated and narrow definition of "high-skilled" talent. The Commission's definition of "highly qualified migrants" focuses on those with "higher professional qualifications" who seek formal employment, limiting pathways into AI careers. This definition would exclude individuals upskilled in AI through bootcamps, online courses, or other non-traditional educational pathways—precisely the type of diverse talent pool needed for a vibrant AI ecosystem. In our forthcoming paper, we propose a novel three-category classification framework for technical AI talent that provides much-needed precision to workforce development discussions. The Commission's approach perpetuates traditional immigration criteria based on formal qualifications, employment status, pay ranges and professional categories—metrics that systematically exclude women and minorities due to persistent pay gaps and career trajectory biases. Additionally, current policies view talent as individuals rather than ecosystems, ignoring that professionals move with families and create demand for services across all kinds of sectors and skill levels. 

Second, the plan misses a significant opportunity to capitalize on Europe's existing advantage in gender diversity within technical AI roles. While countries like Finland (39%) and the Czech Republic (31%) demonstrate stronger female representation in technical AI positions than global competitors, the Commission fails to propose concrete measures addressing the severe "leaky pipeline" our research has documented, where this representation drops dramatically at leadership levels. The plan's brief mention of "incentivizing the return of European AI talent to the EU" lacks substantive mechanisms or understanding of why European talent leaves in the first place. With President Trump's opposition to immigration and campaign against diversity efforts creating uncertainty for international talent in the US, Europe has a strategic opening to attract diverse talent—particularly women in tech who may seek more inclusive environments. Yet the plan lacks targeted retention policies addressing systemic biases in evaluation and promotion that would make such returns sustainable. 

Perhaps most concerning is the geographical mismatch between infrastructure and talent. While establishing 13 AI Factories across 17 Member States, as the Commission proposes, sounds impressive, our data reveals that 10 of these facilities are not close enough to existing AI talent pools. This creates substantial challenges for talent acquisition and retention, as each isolated factory must develop custom talent attraction strategies, competing not only globally but also with other European hubs, sometimes even within the same national context. The plan offers no targeted support for talent development in these regions, risking significant operational delays and underutilization of expensive infrastructure investments. 

Europe risks building AI factories that stand partially empty

Europe has legitimate aspirations to lead in AI, and the Commission's investments in computing infrastructure are necessary prerequisites. However, without addressing these fundamental talent strategy gaps, Europe risks building expensive AI factories that stand partially empty—or worse, serve primarily as training grounds for specialists who ultimately build their careers elsewhere. A truly comprehensive AI strategy must match investments in silicon with equally sophisticated investments in the human capital that enables AI development and deployment. 

Our research on AI talent ecosystems offers a more nuanced framework for understanding these challenges and developing evidence-based solutions. As Europe embarks on this important journey, we hope the Commission will supplement its infrastructure focus with a deeper engagement on talent strategy—the key determinant of whether Europe becomes a global AI leader or merely an AI training ground for other regions.