Amidst the increasingly fierce global competition in artificial intelligence (AI), Europe, as a region with a concentration of traditional technological and industrial powers, is perceived by many observers as temporarily lagging behind China and the United States in AI development. To promote AI development, Europe has been making frequent moves since 2025, attempting to occupy a position in the global AI landscape through policy guidance and capital injection.

Strategic implementation in full swing

According to the "Artificial Intelligence Index Report" by Stanford University, in 2024, the United States led the world with 40 iconic artificial intelligence (AI) models released globally, followed closely by China with 15, while the European Union had only 3, all of which were concentrated in France. In February 2025, the Artificial Intelligence Action Summit was held in Paris, France. French President Emmanuel Macron repeatedly sent strong signals before and after the summit, stating that "Europe is lagging behind in the field of AI" and emphasizing that financing and relaxing investment regulations are key for Europe to catch up with the gap between China and the United States. During the summit, European Commission President Ursula von der Leyen officially announced the launch of the "InvestAI" initiative, which plans to mobilize 200 billion euros for investment in the AI field; Macron also announced at the same time that he would attract 109 billion euros in private investment to promote the development of France's AI industry. According to a report by the Global Times citing Agence France-Presse, an official from Macron's office stated, "This summit comes at the right time, sounding an 'alarm bell' for France and Europe, and also indicating that Europe is ready to utilize AI technology."

Strategic layouts at the EU level are coming one after another. On October 8, 2025, the European Commission officially released two major strategies: "Applying Artificial Intelligence" and "Artificial Intelligence in Science". The "Applying Artificial Intelligence" strategy focuses on key areas such as healthcare and pharmaceuticals, energy, manufacturing, defense, and communications. It proposes specific measures such as establishing AI-empowered advanced medical screening centers and supporting the development of cutting-edge models and intelligent agents for the manufacturing, environmental, and pharmaceutical industries. The "Artificial Intelligence in Science" strategy positions the EU as an AI-driven center for scientific innovation. Its core is to gather and coordinate AI resources through the virtual research institute "European Artificial Intelligence Science Resources" to facilitate breakthroughs in basic scientific research.

Weaknesses and strengths coexist

Despite the continuous advancement of strategic layout, European AI still needs to overcome multiple structural obstacles to achieve real breakthroughs. Wu Zewei, a special researcher at Su Shang Bank, pointed out that Europe's temporary lag in the AI race is mainly due to multiple structural shortcomings. Firstly, the scale of capital investment in Europe is far inferior to that of China and the United States, and the long-term lack of venture capital has made it difficult for local startups to sustain themselves during the critical stage of technology commercialization. Secondly, there is a significant gap in Europe's computing power resources, with a severe shortage of commercial data center capacity and a low global share of AI servers, which severely restricts its technological research and development as well as model training. Lastly, the European market and ecosystem are fragmented, and there are barriers between member states in terms of strategic coordination and data circulation, making it difficult to form a unified large-scale market and weakening overall competitiveness.

In the process of promoting AI deployment and implementation, Europe faces more specific practical challenges. Wu Zewei stated that the primary obstacle lies in the structural imbalance of technology penetration. Large enterprises have actively embraced AI, but a significant number of small and medium-sized enterprises (SMEs) have significantly lower application rates due to limitations in resources, skills, and data, which severely restricts the overall productivity of AI. Secondly, there is a persistent shortage of key production factors, with high-end AI talent continuously flowing to China and the United States, while the local training system fails to meet industry needs. Thirdly, the rapidly growing demand for AI computing power also poses pressure on Europe's energy network. Finally, the complex regulatory environment and difficulties in internal coordination constitute institutional frictions. In addition, the implementation and coordination of major strategic projects among member states often takes time and effort.

Despite this, Europe still retains its unique advantages. Wu Zewei emphasized that its solid industrial foundation provides abundant scenarios and high-quality data for vertical AI applications, especially in fields such as high-end manufacturing and healthcare, where it has accumulated unparalleled professional knowledge. At the same time, its leading ability to shape rules is another trump card. The strict regulatory framework represented by the "Artificial Intelligence Act" brings compliance challenges, but it also positions Europe at the moral and regulatory high ground in building a credible and ethical AI governance system, with the potential to define global standards.

Overall, in the future, if Europe can enhance its AI technological strength and innovation vitality, and strengthen industrial support, it may have the potential to redefine its role in the global AI landscape.