ZH reported, citing a May 19 report from China Daily.
For years, many multinational technology companies viewed China primarily as a manufacturing base, a sales market or a critical link in global supply chains.
Increasingly, however, global firms are beginning to see something else.
China is becoming one of the world’s most important ecosystems for industrial artificial intelligence.
That shift helps explain why companies such as Dassault Systèmes are expanding their AI partnerships, investment activity and long-term technological presence in China despite rising geopolitical uncertainty between Beijing and the West.
For global technology firms, the logic is becoming difficult to ignore:
Some of the fastest real-world AI innovation is now happening inside China’s industrial economy.
This matters because the next stage of artificial intelligence may look very different from the first.
The global AI boom initially centered on large language models, chatbots and consumer-facing generative AI systems. But increasingly, attention is shifting toward industrial applications — systems capable of improving manufacturing, robotics, logistics, engineering, automation and physical production environments.
And few countries possess China’s combination of manufacturing scale, engineering talent, industrial complexity and AI deployment capacity.
That creates a unique environment for experimentation.
Factories, supply chains, robotics companies, electric vehicle makers and smart manufacturing platforms generate enormous volumes of industrial data that AI systems can learn from. The scale of real-world application scenarios available in China allows companies to test, refine and commercialize industrial AI technologies far faster than in many other markets.
For companies like Dassault Systèmes, China is therefore no longer simply a place to sell software.
It is becoming a place where industrial AI itself is being shaped.
The distinction is important.
Industrial AI differs fundamentally from consumer AI.
A chatbot can tolerate occasional inaccuracies. Industrial systems cannot. AI models used in manufacturing environments must operate within the constraints of physics, engineering tolerances, safety requirements and production reliability. Mistakes can disrupt factories, damage equipment or compromise industrial processes.
That is why many global firms are now investing heavily in what some executives describe as “physical AI” — AI capable of understanding how digital intelligence interacts with real-world industrial systems.
China’s industrial ecosystem offers a uniquely valuable testing ground for that evolution.
The country’s manufacturers are moving rapidly into advanced sectors including electric vehicles, humanoid robotics, industrial automation, smart equipment and electric vertical takeoff and landing aircraft. These industries require increasingly sophisticated integration between software, simulation, sensors, automation and AI decision-making systems.
In many cases, Chinese companies are moving faster than expected.
Executives from multinational firms visiting China frequently describe how local companies are no longer merely catching up technologically. Instead, many are becoming global innovation leaders in areas where rapid iteration, supply-chain integration and large-scale deployment matter more than legacy industrial dominance.
China’s EV industry illustrates this transformation clearly.
Companies such as XPeng are simultaneously developing electric vehicles, robotics and advanced mobility technologies while shortening product development cycles at extraordinary speed. This rapid experimentation environment creates powerful opportunities for AI integration and industrial software development.
For multinational firms, participation in this ecosystem is increasingly becoming a strategic necessity rather than an optional market expansion effort.
The competitive pressure is global.
Companies that fail to engage with China’s industrial AI development risk falling behind in areas such as intelligent manufacturing, robotics integration, digital simulation and advanced industrial software.
That concern partly explains why global partnerships around industrial AI are accelerating.
Dassault Systèmes’ expanded collaboration with NVIDIA reflects a broader industry trend toward combining AI systems with simulation, modeling and industrial data platforms capable of supporting large-scale manufacturing applications.
The objective is not merely smarter software.
It is the creation of “industry world models” — digital systems capable of simulating and optimizing complex physical production environments with scientific accuracy.
China is becoming central to this effort because of its manufacturing depth.
Unlike economies dominated primarily by services or finance, China still possesses extensive industrial infrastructure spanning electronics, machinery, automotive production, robotics, energy systems and advanced materials. AI systems trained within these environments can potentially achieve capabilities difficult to replicate elsewhere.
At the same time, Beijing is actively encouraging this transformation.
Chinese policymakers increasingly view AI integration into manufacturing as essential to upgrading industrial competitiveness and moving the country higher up the global value chain. Government plans targeting industrial intelligent agents, smart factories and AI deployment across manufacturing sectors are reinforcing private-sector investment momentum.
Importantly, China’s role in industrial AI is not limited to domestic companies.
Global firms are increasingly integrating Chinese AI models, engineering teams and local innovation partners into broader international development strategies. Some multinational companies are now testing dozens of Chinese foundation models alongside Western systems to evaluate industrial applications.
This reflects a changing reality in global technology competition.
For years, innovation largely flowed from the West into China.
Now, in some industrial AI domains, learning is becoming more two-directional.
Of course, geopolitical risks remain significant.
Technology restrictions, export controls, data security concerns and rising strategic rivalry between China and Western countries continue complicating cross-border cooperation. Many multinational firms must carefully balance commercial opportunities in China against political pressures at home.
Yet despite these tensions, most global technology companies understand a difficult truth:
The future of industrial AI may be impossible to fully develop without China.
Not simply because of market size.
But because China increasingly provides something even more valuable — a large-scale real-world environment where AI, manufacturing and industrial transformation are converging faster than almost anywhere else in the world.
And in the next phase of global technological competition, that ecosystem could become one of China’s most important strategic advantages.