This week, for a few days at least, Paris has become the central node of the global AI conversation. “Le Chat”, Mistral AI’s new LLM chatbot, has overtaken its American and Chinese counterparts on the Apple Store, in a largely unexpected breakthrough for European tech. The Paris AI summit which began on Monday has attracted tech moguls such as OpenAI’s Sam Altman, as well as politicians ranging from US Vice President JD Vance to European Commission head Ursula von der Leyen.

But the star of the show was Emmanuel Macron, who announced an €109-billion investment package in AI, with 35 sites identified for immediate data centre development, and proclaimed that France was “back in the AI race.”

France has a surprisingly large number of assets in the AI global race. The founders of Mistral AI met in France’s prestigious École Polytechnique engineering school, while the quality of the country’s top engineers is no secret in Silicon Valley or Wall Street. “AI godfather” Yann LeCun was born in the impossibly French-sounding town of Soisy-sous-Montmorency. If France manages to keep these assets home, it will have some of the most skilled foot soldiers in the global AI race.

This effort can be powered by France’s cheap and bountiful nuclear energy, which generates two-thirds of its national energy supply. Deemed to be antiquated not long ago by its political elites — Macron himself had campaigned in 2017 to denuclearise France’s energy production and shut down a nuclear plant — nuclear energy turns out to be invaluable in powering electricity-hungry AI data centres. As Macron quipped at the summit: “I have a good friend in the other part of the ocean saying ‘Drill, baby, drill.’ Here there is no need to drill. It’s just plug, baby, plug.” Despite an ageing nuclear park in dire need of renovation, France exported 90 terawatt-hours of electricity last year and will dedicate one gigawatt of nuclear power for AI.

For Macron, Mistral’s breakthrough is a welcome opportunity. With his minority coalition government hanging by a thread over acrimonious budget discussions, and as he increasingly resembles a lame duck ahead of the 2027 presidential elections, the French President will be looking for some bold projects to establish his legacy.

This desire was fully apparent in Macron calling for a “Notre-Dame Strategy” for AI in France and Europe, referring to the rapid reconstruction of the cathedral after the hugely destructive 2019 fire. Yet this comparison also highlights lingering structural barriers to France’s economic development. The reconstruction of Notre-Dame in only five years was a small miracle, but one made possible by the French state deciding to waive much of the red tape and bureaucratic hindrances that have smothered other ambitious projects. Only last year, a semiconductor factory saw its extension project blocked in Grenoble over environmental concerns.

Another potential self-imposed constraint on Macron’s AI ambitions will come from the EU. The mantra is now well-known: America innovates, China replicates, and the EU regulates. Only a few days ago the EU seemed doomed to watch Beijing and Washington dominate the tech race, with the Brussels AI Act its only contribution to this struggle. In the last few months, though, the EU’s regulatory passion has been under fire, with former Italian prime minister and European Central Bank president Mario Draghi lambasting it in a landmark report. It remains to be seen how the AI Act — a fantastically dense and complex piece of legislation — will impact the development of AI in the EU.

What’s more, France lacks the financial firepower of the US to push these large projects. For all of Macron’s celebration of Le Chat as a tool for European tech sovereignty, most of the €109-billion investments announced are coming from foreign funds; €50 billion alone will come from the United Arab Emirates. In recent years, many French tech start-ups have hopped over the Atlantic to tap into the much larger American capital market.

With budget negotiations looming in the background, and with a return to the EU target of a 3% deficit nowhere in sight, this AI breakthrough constitutes a painful reminder for French elites. The inability of the political class to clean up its finances means that the country lacks the fiscal space to deal with tomorrow’s crises, or to invest properly now in the technology of the future.

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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