Europe is charting a unique course in artificial intelligence, one that diverges from the commercial-centric strategies of the United States and the industrial-scale dominance of China, according to Diego Perino, director of the AI Institute at the Barcelona Supercomputing Center (BSC). Perino emphasized that Europe’s approach is rooted in its research infrastructure, public data governance, and long-term structural capabilities, rather than single commercial breakthroughs.

AI Ecosystem vs. Product-Centric Models

During an interview with Yicai at the Mobile World Congress in Barcelona, Perino outlined how Europe is building an open and transparent AI ecosystem. Unlike the U.S., which relies heavily on private tech firms, or China, which benefits from strong industrial scale, Europe is focusing on foundational models and computational infrastructure that support innovation across research and public institutions.

“Europe’s role is not about building a single commercial product but about building an ecosystem,” Perino said. “We are developing open, transparent, and auditable foundational models that serve as a base for researchers, public institutions, and small and medium enterprises to innovate upon.”

At the MWC, AI emerged as a central theme across nearly every exhibition hall. Generative AI, AI agents, and AI-driven software systems were on full display, highlighting the rapid expansion of the technology’s influence across industries.

Europe’s Strength in Long-Term Structural Capabilities

Perino noted that Europe’s strength lies not in singular technological breakthroughs but in its long-term structural capabilities. The BSC, established in 2005, is Spain’s national center for high-performance computing and one of Europe’s leading institutions in supercomputing and computational science. It operates the MareNostrum supercomputer, one of the most powerful systems on the continent.

The BSC has expanded its research into climate science, biomedicine, engineering simulations, and AI in recent years. Its AI Institute is working to advance open foundational models and support the development of Europe’s AI ecosystem through initiatives like AI Factories, which help train and deploy large-scale AI models.

“Our goal is not to build a single commercial product, but rather to support the development of the broader ecosystem,” Perino said.

Europe’s AI strategy also benefits from a strong talent base, with many highly qualified researchers trained in the region. Additionally, Europe has a wealth of datasets with strong local characteristics, which can be used within its legal frameworks to develop AI systems with distinctive features.

However, challenges remain. One of the key issues is fragmentation. While Europe has many research programs and innovation initiatives across countries and institutions, achieving stronger coordination on a larger scale remains a hurdle. Another challenge is private investment, which lags behind the U.S. in frontier AI technologies, despite Europe’s strong public funding mechanisms.

Regulation as a Differentiating Factor

Europe’s emphasis on regulation and “Trustworthy AI” has raised questions about whether it could hinder innovation. Perino, however, sees this as a strength. He said Europe’s focus on safety, transparency, and alignment with social values reflects its broader cultural and institutional context.

“I do not see regulation as a barrier. In the long run, if designed well, regulation can actually become a differentiating advantage,” Perino said. “Building AI systems that are aligned with European laws and values is itself part of Europe’s development path.”

As AI models continue to grow in scale and complexity, computing power, data, and talent are becoming key foundations of national AI strategies. Europe’s high-performance computing infrastructure, including initiatives like AI Factories, is critical to its AI development.

“Computing power is a necessary condition. Without sufficient computing capacity, it is impossible to train or deploy large-scale models,” Perino said. “High-performance computing infrastructure is therefore extremely important for AI development. However, simply increasing computing power is not enough. AI progress also depends on advances in algorithms and architectures.”

Perino highlighted the importance of continued investment in fundamental research alongside expanding computing capacity. The BSC AI Institute, he said, is focused on developing open, auditable foundational models aligned with European values and supporting the adoption of AI by SMEs and public institutions through practical applications and real-world use cases.