Whoever observes China only as the world's factory is still looking at a country that no longer exists. Over the last few decades, the Asian giant has become a continental-scale laboratory, capable of designing proprietary chips, training foundation AI models, creating vertical digital ecosystems, and putting applications into operation for hundreds of millions of people in a matter of weeks. It's more than technology: it's culture, strategy, and execution.
I was able to observe all of this up close, and I participated in an in-person immersion at companies such as Huawei, Alibaba Cloud, Meituan, Kwai, SenseTime, and NIO, as well as at innovation centers in Beijing, Hangzhou, and Shanghai. I also participated in the 8th World Artificial Intelligence Conference (WAIC), which brought together global leaders around the theme "Global Solidarity in the AI Era." Field experience allowed me to observe how technology, culture, and strategy intertwine to create impact on a national scale.
The Chinese gear begins long before the first prototype. Culture and education are at the center. In a country that was never colonized and carries more than five thousand years of history, trust relationships are built slowly, but execution, when decided, is swift. The work proceeds at an intense pace (the famous 9/9/6 model) and education is treated as a strategic vector of innovation, with pressure and investment to train talents at an extremely high scale.
This cultural base aligns with a business and governmental ecosystem that operates in a coordinated manner. A Huawei, for example, allocates 20% of its revenue to R&D and develops its own AI models; Alibaba Cloud verticalized its entire technology stack and created the Qwen family of models; Meituan handles 150 million daily orders by combining multiple services in a super app; and Kwai already connects more than 60 million users in Brazil to social commerce, a phenomenon that in China accounts for more than 25% of e-commerce. Models like the X27 (shopping turned into a mega live-commerce studio) and vehicles like those from Nio, with batteries removable robotically in 3 minutes (BaaS system,battery as a service) and integrated virtual assistants illustrate how innovation permeates entire sectors.
What is impressive is not only what China creates, but the speed and scale with which it applies it. AI models trained for specific sectors go into operation quickly, and autonomous agents are already present in retail, healthcare, mobility, and public administration. All of this is sustained by a data infrastructure and a digital penetration that surpasses 99% of the population.
Brazil, on the other hand, advances in a more fragmented way. We have technical talent, creativity, and a sizeable domestic market, but we face structural barriers: slower regulatory frameworks, R&D investments still modest, and limited integration between government, businesses, and the university. Our digitalization is advancing, but not with the same degree of technological verticalization and without a robust national strategy that coordinates sectors and defines long-term priorities.
Of course the Chinese model cannot be simply replicated. He is deeply rooted in his history, in his political system, and in his culture. But there are clear lessons: invest heavily and continuously in research; think of technology as a sovereign asset; create mechanisms for companies to innovate not only in products, but in infrastructure and standards; and, above all, coordinate efforts in a coordinated manner, understanding that digital competitiveness is built with a decades-long vision, not of mandates.
The world is moving toward an era in which artificial intelligence, data integration, and applied innovation will define not only markets, but also the place of each nation on the geopolitical map. China has already understood this and is carrying it out. Brazil has the basis to learn quickly and apply with ambition. How do we implement, with coordination and speed, what has already been proven to gain global competitiveness?
Gustavo Pinto is a senior researcher at Zup Labs, a division dedicated to research and development (R&D) in Generative Artificial Intelligence, where he conducts applied research focused on Zup, a technology company that is part of the Itaú Unibanco group, and its clients. PhD in Computer Science from UFPE, Gustavo is the author of more than 100 scientific articles in the field of software engineering.
