Introduction
While the Western world holds endless debates about ChatGPT, AI governance, and existential risks, China is quietly and systematically building something far more ambitious: an artificial intelligence ecosystem rooted in national strategy, industrial policy, and civilizational vision.
At the recent Expert Talk hosted by the Madrid Innovation Lab, two leading voices on Chinese tech innovation—entrepreneur Wang Guanchun and Claudio Feijoó—unveiled the intricate architecture of China’s AI machine. Their insights, drawn from years of experience inside the Chinese innovation system, suggest that China is not merely trying to compete with Silicon Valley—it is building something entirely different.
1. The Three Pillars of Chinese AI Dominance: Compute, Data, Talent
Claudio Feijoó, who has collaborated with top Chinese universities for nearly a decade, outlined what he called the «recipe» for AI supremacy: computational power, high-quality data, and a robust talent pool.
Computational Power: While U.S. sanctions have sought to restrict China’s access to top-tier chips, companies like Huawei have developed competitive alternatives such as the Ascend processors. Even before restrictions tightened, Chinese tech giants stockpiled the needed GPUs. In essence, China has prepared for this tech war.
Data: With fewer privacy restrictions compared to the EU and a proactive stance toward data sharing, China has a significant advantage in training large-scale models. New platforms are being built to facilitate inter-sectoral data exchange, recognizing that data is the new oil—and no one wants to give it away freely.
Talent: Perhaps the most underestimated strength. Unlike in the past, where Chinese engineers would go abroad to train, today many are educated domestically at top institutions and universities. The DeepSeek model, built entirely by locally trained engineers, proves that China no longer needs to rely on foreign-trained experts to lead in AI innovation.
“China isn’t just building AI. It’s building an AI civilization.”
2. Industrial Policy: AI with Chinese Characteristics
Whereas Western innovation is largely market-driven, China’s approach to AI is coordinated through a powerful blend of state support and entrepreneurial dynamism.
The Chinese government acts on both the supply side (providing resources like computing infrastructure, talent pipelines, and R&D funding) and the demand side (deploying AI in cities, public services, and industry). This dual strategy creates rapid adoption cycles and ensures that AI is integrated into the fabric of daily life.
Feijoó highlighted the city of Hangzhou 杭州 has a striking example: a fertile environment where local governments are supportive, universities are competitive, and companies are hungry to innovate. The result? Breakthroughs like DeepSeek emerge not from Beijing or Shanghai, but from these agile innovation clusters.
3. Flexible Regulation: Gray Zones that Foster Innovation
China’s regulatory approach is paradoxical: on the one hand, it draws red lines for ideological and political content; on the other, it allows wide experimentation in technical and commercial domains.
This approach favors agility. The absence of a centralized AI agency means regulators can move slower than the market, enabling entrepreneurs to push boundaries. Consumer protection exists, but it is not the priority. What matters most is innovation, speed, and alignment with national goals.
“In China, regulation is patchy by design. The gray zone is where the magic happens.”
Furthermore, China is positioning itself as a regulatory model for the Global South. Unlike the U.S., which is often viewed with suspicion, China offers a narrative of AI development that respects national sovereignty and non-interference. This resonates with many countries looking for alternatives to Western digital hegemony.
4. Geopolitical Stakes: AGI, Supremacy, and Divergent Futures
As the conversation turned to AGI (Artificial General Intelligence), a chilling thought emerged: what if one country develops a superintelligence that ensures its dominance for a century?
Feijoó posed a thought experiment: if you knew another nation was on the brink of developing AI, would you wait idly, or act to prevent them? This logic of technological supremacy echoes nuclear deterrence theory.
In this race, divergence matters. U.S. models may prioritize creativity and openness. Chinese models could embed collectivist ethics and long-term stability. As chip sanctions push China to build its own hardware, we may soon see entirely different AI paths—not only technologically, but civilizationally.
“We may be headed not for a single AI future, but for multiple, fragmented AI realities.”
5. Lessons for Europe: Between Two Worlds
Europe is caught between two superpowers, both advancing AI at breakneck speed. But rather than simply copying U.S. frameworks or fearing China’s advances, Europe might find inspiration in China’s strategy:
- Invest in talent locally, not just rely on Silicon Valley elites.
- Use industrial policy to coordinate public and private interests.
Embrace open-source ecosystems to balance innovation and sovereignty.
The city of Madrid, with projects like the digital twin and AI-powered urban systems, is already moving in that direction. But the real challenge is cultural: are we willing to imagine AI not just as a tool, but as part of a broader vision of society?
Conclusion: The Silent Powerhouse Has a Voice
China’s AI trajectory is not accidental. It is the result of deliberate policy, local innovation clusters, talent development, and geopolitical awareness. While Western narratives often reduce China to a threat, the truth is more complex—and far more consequential.
As a European observing China not just from the outside, but from the inside of a global tech transformation, I see not just rivalry—but possibility. Perhaps the future is not about choosing sides, but about understanding the full map.
And China, quietly and methodically, is redrawing it.
© Picture: Madrid Innovation Lab MIL
@Yolanda Muriel 
yolandamuriel.com 