Is AI Bringing the EU and China Closer?

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Introduction: the Evolving Landscape of AI Governance

In the early 1950s, computer scientist Alan Turing sparked a technological and philosophical revolution with a deceptively simple question: "Can machines think?" Today, this once-abstract query has evolved into a complex geopolitical challenge, with artificial intelligence (AI) at the center of a global race for technological supremacy. AI has rapidly progressed from theoretical concepts to sophisticated foundation models—AI systems trained on vast datasets—enabling breakthroughs in generative AI. Tools like OpenAI's ChatGPT in the U.S. and China's DeepSeek can now write novels or design proteins, learning patterns from trillions of data points to produce human-like outputs.

Three major players are shaping the future of AI and its governance: the United States, where innovation is largely driven by tech giants; China, pursuing state-directed AI development; and the European Union, striving to balance regulation with innovation. 

The EU and China initially followed divergent paths. Yet, the February 2025 AI Action Summit in Paris marked a significant shift in this landscape: 61 nations, including the EU and China, endorsed a joint statement on "inclusive and sustainable AI," while the United States and United Kingdom abstained. This alignment between Brussels and Beijing raises crucial questions about the future of AI governance: What factors drove this unexpected convergence, and what are the implications for global tech policy?

Divergent Path: The EU and China's Distinct AI Strategies

The European Union and China have historically adopted divergent strategies in their approach to technology development and regulation, and AI is no exception. The EU’s  approach to AI has been characterised by a human-centric focus, emphasising caution and ethical considerations to ensure public trust. This stance was significantly influenced by the Cambridge Analytica scandal in 2018, which exposed the potential for algorithmic manipulation of democratic processes. The scandal revealed how personal data harvested from Facebook was misused for targeted political advertising, raising serious concerns about the ethical implications of AI and data-driven technologies.

In response, the EU prioritised ethics in its digital and data strategy, implementing a series of landmark initiatives, including the General Data Protection Regulation (GDPR), the Digital Markets Act, and the Digital Services Act. These efforts culminated in the EU AI Act of 2024, the world’s most comprehensive legislation on AI governance, which bans high-risk AI applications (e.g., social scoring and biometric categorisation) and mandates transparency for AI systems – a stark contrast to China’s surveillance focus. This strict regulatory framework has raised concerns about potentially increasing the innovation gap between Europe and other key players in the AI race. Seeking to address this imbalance, European Commission President Ursula von der Leyen announced at the AI Action Summit the launch of InvestAI, a €200 billion initiative designed to mobilise capital for AI infrastructure (e.g., AI gigafactories) and support emerging startups. Nevertheless, Europe still lags behind its Asian counterpart in terms of private sector investment, investing approximately €12 billion annually versus China’s €30 billion in 2023. 

China, conversely, has pursued a state-driven strategy aimed at global AI leadership. The 2017 Next Generation AI Development Plan set ambitious goals for AI development, targeting global AI dominance by 2030 through significant state investment in key sectors like facial recognition and quantum computing. This approach has yielded results, with China being responsible for more than 38,000 patent families between 2014 and 2023, publishing more AI patents each year than all other countries combined, according to the World Intellectual Property Organisation. In order to achieve its goal, China’s approach emphasises control over innovation, as AI development is tied to national security, with strict data localisation and censorship laws (e.g., algorithmic “social credit” systems). 

This centralised approach has enabled China to make rapid advancements in AI, but it also raises concerns about privacy, surveillance, and ethical considerations. For instance, facial recognition technology has been deployed for mass surveillance in public spaces, often without consent, while the social credit system has been criticised for potentially penalising individuals based on opaque criteria and algorithmic assessments. Moreover, the lack of transparency in how data is collected and used, especially in regions like Xinjiang, has drawn international scrutiny and raised alarms over the use of AI to suppress dissent and enforce ideological conformity.

The Paris Summit: a Convergence of Players

The 2025 Paris AI Summit brought these contrasting approaches into sharp focus, revealing a surprising degree of alignment between the EU and China. Several factors contributed to this convergence.

First, there are existing shared concerns over U.S. tech dominance. Both parties share apprehensions about the concentration of AI capabilities in American firms, thus fearing exclusion from a U.S.-led AI ecosystem. The U.S. company NVIDIA alone controls approximately 70% of the advanced AI chip market, with other U.S. companies like AMD and Intel following behind. The United States is also a dominant player in foundational model development; in 2023, it developed a total of 61 notable machine learning models, significantly outpacing China's 15. In that sense, the EU and China have a shared incentive to balance U.S. power, viewing its tech dominance—exemplified by companies such as OpenAI and NVIDIA—as a potential threat to their sovereignty.

Second, both the EU and China share a common interest in promoting open-source AI models as alternatives to proprietary, closed-source systems developed by U.S. tech giants. Open-source AI allows for greater transparency, collaboration, and innovation by making the source code freely accessible and modifiable. The EU has backed initiatives like Mistral AI, a French startup whose model competes with larger U.S. counterparts despite limited resources. Similarly, China supports DeepSeek, whose open-source DeepSeek R1 model offers comparable performance to GPT-4 at a fraction of the training cost. This shared emphasis on open-source AI serves multiple purposes: it reduces dependence on U.S. technologies, aligns with respective governance models, and potentially democratises AI development.

Third, there is a shared ambition to exert a prominent role as a regulatory authority. With the U.S. stepping back from global AI governance discussions, both the EU and China see an opportunity to shape international standards and gain more influence, despite their different motives. The EU’s AI Act and China’s domestic standardisation efforts reveal a tactical overlap in leveraging technical norms for influence. This attempt is even more relevant now that the Trump administration’s 2025 AI deregulation executive order from last January prioritised corporate innovation over governance, isolating Washington from international cooperation in global AI governance.

Moreover, this alignment can also be understood through economic pragmatism. The EU and China share a deeply interwoven trade relationship, standing at €739 billion in 2023, that increasingly centres on sectors where AI is becoming indispensable, such as renewable energy, electric vehicles, logistics, and healthcare. This strong economic interdependence creates both the need and the opportunity to cooperate in AI-related domains. For example, European firms operating in China may benefit from better access to local AI solutions for supply chain optimisation or predictive maintenance, while Chinese companies can tap into Europe’s regulatory expertise in trustworthy AI to enhance their products’ appeal in global markets. These shared incentives foster practical reasons to align on common technical standards, research initiatives, or regulatory frameworks, even if broader strategic goals diverge.

Persistent Challenges and Fundamental Differences

Despite the apparent convergence at the Paris Summit, significant obstacles to sustained EU-China cooperation on AI governance remain. The most prominent challenge is the fundamental difference in their approach to values and human rights, which leads to a significant divergence in approaches to data privacy and AI ethics. The EU's emphasis on privacy and individual rights, enshrined in regulations like GDPR and the AI Act, contrasts sharply with China's use of AI and data for social monitoring and surveillance policies.

Another important factor to consider is the divergent emphasis they place on achieving technological sovereignty. Both parties aim to reduce dependence on U.S. technology, but they pursue this goal through different means. The EU's €200 billion InvestAI initiative focuses on developing domestic AI capabilities within a regulated framework, while China's $47 billion semiconductor push aims to circumvent U.S. export restrictions.

Of equal importance is their contrasting approaches to the military applications of AI. The EU advocates for restrictions on autonomous weapons systems, particularly lethal autonomous weapons, as part of its ethical AI framework. In contrast, China is actively integrating AI into its military technologies and defense systems. Specifically, the People's Liberation Army (PLA) is focusing on developing AI-enabled capabilities in several key areas, such as AI-enhanced missile sensors to improve accuracy and exploring the use of generative AI for wargames and training operations.

Europe's Dual Role: Balancing Regulation and Innovation

The EU faces a challenging balancing act between maintaining its role as a global leader in AI regulation and fostering a competitive AI industry. Critics argue that strict regulations like the AI Act may hinder innovation, creating a threefold competitive advantage for providers and developers operating in jurisdictions with lower or no regulatory standards. These entities benefit from reduced costs, shorter timeframes, and the ability to pursue innovative and unregulated approaches. Moreover, by banning external providers and developers from deploying high-risk applications in the EU, the AI Act may inadvertently deprive the EU market and its citizens of potentially beneficial AI-based products and services, ultimately diminishing overall welfare within the EU.

However, proponents of the EU's approach argue that by setting high standards, Europe is creating a framework for trustworthy AI that could become a global benchmark. The adoption of EU-style AI regulatory approaches by countries like Japan, South Korea, Brazil, and some U.S. states lends some credence to this view.

Conclusion: a Pragmatic Alignment with an Uncertain Future

The EU-China alignment on AI governance at the Paris Summit represents a pragmatic response to the current global tech landscape rather than a fundamental shift in relations or a value-based alliance. Both parties recognise the value of cooperation in order to counterbalance U.S. hegemony in AI development and to project themselves as influential actors in AI standard-setting. For the EU, the main advantage lies in engaging with China as a way to maintain influence in the evolving global AI landscape, particularly by helping shape technical standards, gaining exposure to large-scale AI applications, and ensuring interoperability in key sectors, while continuing to strengthen its own AI capacity. For China, cooperation creates political and regulatory conditions that may facilitate access to European markets—particularly by aligning technical standards and reducing regulatory barriers. This could enable Chinese firms to operate more easily within the EU's AI ecosystem, participate in joint research initiatives, and increase their commercial presence, all while potentially diluting U.S. influence.

However, the sustainability of this alignment remains uncertain. The success of Europe's InvestAI program in fostering innovation while maintaining ethical standards, and China's ability to gain international traction for its AI models without Western semiconductors, will be crucial factors in shaping the future of this relationship. Europe struggles to balance its dual role as “global regulator” and “AI competitor,” while China views cooperation as a tool to access Western markets and talent.

What is clear is that as AI continues to advance rapidly, the need for global governance frameworks becomes increasingly urgent. Its proliferation amplifies existing risks such as deepfakes manipulating public opinion, AI-powered voice scams and financial fraud, job displacement due to automation, the massive spread of AI-generated disinformation, ethical and legal challenges from autonomous decision-making, perpetuation of algorithmic biases, and the potential misuse of AI in military applications—all of which threaten social stability, economic security, and international peace. In this context, Brussels and Beijing will continue their delicate dance—partners in challenging U.S. dominance, rivals in defining humanity’s technological future. Their dialogue on AI, despite its inherent limitations, may prove to be an important step towards more inclusive international cooperation in this critical field.

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ABOUT THE AUTHOR

Cristina Martín Rodrigo is a writer for European Guanxi and a final-year student in the Double Bachelor’s Degree in International Relations and Corporate Communication at King Juan Carlos University in Spain. She is passionate about Asia, particularly East and Southeast Asia, and has worked on academic projects exploring countries such as China, Cambodia, and Mongolia. Cristina’s academic focus includes sustainability, human rights, and global ethics. She is currently working on her final thesis projects, one analyzing the strategic narratives of BRICS and the other examining the environmental and human rights impacts of China’s Belt and Road Initiative on Southeast Asian communities. In addition, she has professional experience in Internal Communications and CSR in different sustainability-driven companies.

This article was edited by George Banos and Agnes Monti.