Interview with Atlantico on France’s AI Infrastructure investments, following the 2026 Choose France Summit announcements (Excerpts).
Are the Choose France announcements a sign that France is winning the AI race—or just the data center race? Behind the €93 billion figure, how much actually goes toward developing AI technologies, models, and intellectual property compared to infrastructure?
These investments do not mark a decisive victory for France in the AI race, but they do position the country at the heart of Europe’s AI infrastructure. While they bring industrial benefits, the creation of intellectual property largely remains in the hands of international players. The challenge now is to leverage this attractiveness to develop a national AI industry.
Amid an energy crisis, France—with its largely decarbonized electricity and stable grid—has become a European hub for AI infrastructure, drawing in players like SoftBank, Brookfield, and Ardian. These firms are investing in data centers and sparking industrial partnerships. Schneider Electric, for instance, is mobilizing its expertise in energy efficiency, cooling, and automation. These projects help develop high-performance data center management skills.
However, the development of key technologies and models remains limited. Despite initiatives like the Bull/Foxconn project on motherboards, the focus is more on infrastructure than R&D labs or GPU production—the latter being where much of the sector’s real value lies. Europe still lags far behind in semiconductors, despite some promising efforts.
We must also consider the financial exuberance surrounding AI, particularly in infrastructure financing. A national strategy cannot be built on speculative promises alone. As seen in global initiatives, France should develop local funding sources and protect the integrity of its tech companies, both in terms of intellectual property and capital resilience.
We often distinguish between inference data centers (which execute queries) and training data centers (where large AI models are developed). Is France hosting the most strategic parts of the value chain, or mainly data centers that benefit from our energy advantage?
Overall, the projects cover both types, though the distinction isn’t always clearly defined. The Ardian/Verne “AI Gigafactory”—combining high-performance computing and research activities—appears to be the most training-focused. Training centers are more strategically valuable from a geopolitical and industrial standpoint, as they require massive resources (energy, cooling, GPUs) and are difficult to relocate.
Inference data centers, on the other hand, are less strategic since they rely on pre-trained models and optimized chips. Yet they complement France’s offering by enabling large-scale AI service deployment with reduced latency for European users. Their value lies in proximity to end markets.
The key challenge is avoiding the role of a mere host. France must capitalize on these infrastructures to develop technological partnerships, attract R&D centers (by conditioning support on technology transfer commitments), build ties with local industry (for sector-specific models), and ensure it doesn’t remain just a provider of electricity and land.
Arthur Mensch, Mistral AI’s CEO, told the National Assembly that AI is first and foremost a heavy energy industry. Does France truly understand that the AI battle won’t be won on talent or software alone, but on the ability to produce and deliver electricity? Can France meet the electrification challenge posed by AI’s demands?
Mensch rightly reminded policymakers that AI isn’t just about models—it’s about physical and energy infrastructure. Behind every model lie data centers, semiconductors, cooling systems, and power grids. Beyond leveraging France’s tradition of mathematical creativity and its versatile engineers and researchers, the country must also exploit its abundant, stable, and competitive electricity supply. Here, nuclear power remains a key advantage, even if the sector has been weakened by strategic indecision and hindered by a flawed European pricing framework.
Why does France face a two-year window of opportunity in AI? Are we witnessing an industrial revolution where today’s decisions will shape global power dynamics for decades?
We’re entering a phase of consolidation. The early years of generative AI were experimental—models were developed, pricing was fluid. Now, the players controlling compute, data, talent, and energy are locking in their positions. The parallel with industrial revolutions is clear: those who dominate foundational infrastructure set the technological, financial, and geopolitical standards that follow.
Yet we must resist the dominant narrative. We’re in an era of excessive valuations, with circular financing mechanisms between semiconductor companies, hyperscalers, and model providers. Many use cases remain unproven, while markets anticipate massive future revenues—even as some models continue to operate at a loss.
Europe shouldn’t blindly copy the U.S. hypergrowth model, fueled by deep capital markets and a high tolerance for deficits. We lack the financial firepower and the same risk appetite. Instead, we must pursue more selective, industrial, and efficient pathways.
Open source is a strategic lever: it enables cost-sharing, broader access, reduced dependence on American platforms, and the development of specialized models without requiring tens of billions in capital. As Yann LeCun has noted, much of Meta’s early Llama development happened in Paris. The real challenge is turning conceptual strength into industrial power.
According to estimates, AI could require up to 40 additional gigawatts of power in France. Should nuclear be seen as the absolute condition for digital sovereignty, or is a more pragmatic mix—nuclear, solar, renewables, and grids—now unavoidable?
Nuclear is essential if France wants to maintain a controllable, decarbonized, and competitive electricity supply at scale. Industrialized AI cannot rely excessively on intermittent energy sources. But the challenge extends beyond nuclear: it’s about the entire energy system—grids, storage, hydropower, energy efficiency, and cooling capacity.
Meanwhile, China is taking a more pragmatic approach: lower-cost infrastructure, more compute-efficient models, and aggressive hardware optimization. Beijing is also working to replicate Nvidia’s capabilities in the face of U.S. export restrictions.
The global AI race is now moving at a pace incompatible with France’s bureaucratic inertia—not just in energy, but across the board. We need to recreate industrial and technological free zones: streamlined regulations and tailored tax incentives for innovation and critical infrastructure. The French paradox is that we once had one of the world’s most competitive energy and scientific systems, only to then systematically deindustrialize ourselves.
Is France missing the AI value chain upgrade, left providing only energy, infrastructure, and expatriated talent while the U.S. captures the real value?
The risk is real: France could end up confined to the lower rungs of the value chain—supplying power, hosting data centers, and exporting talent—while the U.S. monopolizes the high-value segments. But to reposition ourselves, we must first understand the sector’s current state, with its flaws and emerging opportunities.
Beyond the inherent limitations of LLMs, much of the AI sector today is driven by highly speculative financial expectations. Many use cases remain difficult to monetize, even as compute and capital demands skyrocket in the age of agentic AI. The next wave may well come from AI deeply integrated into real industrial systems: robotics, automation, maintenance, defense, logistics, industrial simulation, and healthcare. The goal isn’t just to imitate OpenAI but to drive productivity gains through integration with physical production chains.
With OpenAI’s rumored IPO at $850 billion, Anthropic at $900 billion, and SpaceX at $2 trillion, American giants will have the capital to lock in compute capacity and energy resources at a scale Europe can’t match. Is there still a realistic path for France and Europe to close the AI gap with the U.S. and China in the next two years? Could robotics be part of the solution?
These valuations underscore America’s financial dominance. These companies can raise sums that secure semiconductors, data centers, and energy contracts on a scale beyond Europe’s reach.
Europe has also trapped itself in a regulatory labyrinth, particularly with the AI Act. Multiple European states and companies have pleaded for adjustments to preserve industrial competitiveness—only to see their concerns overlooked. Meanwhile, Donald Trump merely had to demand that Ursula von der Leyen fall in line with U.S. interests—and she complied.
France and Europe can still build strong positions in areas where we have industrial, scientific, or even energy advantages. Robotics is a prime example: it combines software, sensors, mechanics, power electronics, and industry—even if we don’t cover every link in the chain.
Physical AI offers an alternative to consumer-focused, chatbot-driven applications. Advanced industrial robotics delivers direct gains in competitiveness, productivity, and reindustrialization. This is likely where we have the best chance to create synergies with our industrial base.
Read the full interview on Atlantico.