Where AI meets manufacturing: China’s next investment frontier
Key takeaways
China's manufacturing scale, engineering talent, and domestic AI development are creating investment opportunities across its industrial base.
- Investment opportunities span China's AI ecosystem, including power infrastructure, semiconductors, large language models, AI applications, robotics, and factory automation equipment.
- China leads the world in industrial robot installations, and its manufacturing data can feed back into AI model improvements for robotics, smart factories, and autonomous logistics.
- China's approach favors AI as a productivity tool for workers rather than a labor replacement, aligning AI and robotics deployment with sectors facing labor shortages amid a declining working-age population.
China’s huge industrial base, extensive engineering talent and domestic AI capabilities are creating a distinctive set of opportunities for investors.
Every powerful new AI model to emerge from China generates fresh speculation about whether the balance of power in AI is shifting. But for investors, a potentially more consequential opportunity may lie in how Chinese manufacturers implement AI and scale it across the world’s largest industrial base.
Underpinning that opportunity is the country’s human talent.
“China has a massive pool of relatively high-quality engineers at globally competitive costs,” said Viking Huang, CFA, Investment Director of Sunway Communication, a Shenzhen-listed company that designs and produces radio frequency (RF) connectivity and performance-critical electronic components and is expanding into AI infrastructure hardware. He described this as an engineering dividend, as opposed to the labor-cost advantage that had supported China’s manufacturing growth in earlier decades. “This is not about cheap labor; it is about cost-effective R&D velocity.”
How does the size of China’s manufacturing base impact AI adoption?
Grace Tam, CFA, Deputy Chief Investment Officer Asia at BNP Paribas Wealth Management, said China’s manufacturing scale could create a powerful feedback loop between AI models and their industrial use cases.
“China can generate huge amounts of real-world data and turn that into tools for robotics, smart factories and autonomous logistics,” she said. “With that much real-world data, it feeds back into model improvements. This is actually very powerful.”
This builds on something China has been doing for years: deploying AI to a wide range of real-world use cases.
Well before the current enthusiasm for generative AI, China was using AI and data-intensive technologies across sectors including manufacturing, healthcare, transportation and energy. The breadth and depth of that adoption could give Chinese companies an advantage as AI moves into more physical applications. Lower-cost technology can encourage wider adoption, while greater use generates more data to further improve applications and models.
China also has a clear stance on how AI is deployed in industry. Xueshi Bai, CFA, Deputy Director of Beijing International Wealth Management Institute, said the structural, stressed that the country’s approach to AI is focused on augmenting workers and improving productivity, rather than simply replacing labor.
“We make AI a co-pilot for our workers, so we have a more stable employment market, and we have more support from the public for AI development,” said Bai.
China’s approach also reflects pragmatism in the face of its demographic reality. The country’s working-age population has been declining for over a decade, creating pressure to raise productivity as the labor pool shrinks. Its latest five-year plan calls for AI and robotics to be deployed in sectors facing labor shortages.
Where do investors see opportunities in China’s AI development?
Tam said investors should look beyond individual AI models to the wider ecosystem supporting their development and deployment.
“It’s the whole of China’s AI ecosystem — the whole supply chain from power infrastructure and semiconductors to the large language models and then the AI applications,” she said.
The hardware side of that ecosystem is already attracting substantial investor attention. Tam said demand remained strong, and supply bottlenecks in areas including semiconductors and power infrastructure could support earnings growth.
Apart from the infrastructure required to run AI, the opportunity also extends to the equipment used to deploy it. This includes companies producing robotics, factory automation equipment, sensors, industrial software and other components.
Companies using AI to improve their own operations could benefit too. China’s experience in designing, manufacturing and integrating complex physical systems could become an advantage as AI moves from the digital world into machines and factories.
“For China specifically, the most valuable investment opportunities are in segments that serve two purposes: enabling AI commercial viability and achieving supply-chain self-sufficiency,” said Huang.
He pointed to supply-chain localization and vertical integration in hardware — for example, moving from discrete components to integrated solutions — as one way to strengthen self-sufficiency. He added that lower costs per token, per inference, and per useful AI task — and a positive return on investment (ROI) on AI applications — would be important to commercial viability.
Huang explained that one way to achieve lower token costs is to use smaller, purpose-built models tailored to specific tasks, requiring much less compute than general-purpose models. He described these “small brain” models as practical and ROI-positive.
Government support can also help lower the cost of adoption. Tam noted that some Chinese manufacturers can access compute vouchers when they need computing resources to train AI models. More broadly, Huang said segments receiving national-level support are more likely to see sustained investment, favorable financing and customer adoption.
“This isn’t about picking winners based on subsidies,” Huang said. “It’s about recognizing that certain technology transitions have structural tailwinds.”
Can China translate AI adoption into economic value?
The value of AI lies in its ability to change the economics of the businesses adopting it. Tam identified three potential sources of value creation: “AI could create value through productivity gains, new business opportunities and improved efficiency across companies.”
That could take several forms. Manufacturers might use AI to automate production, improve quality control or reduce downtime. Logistics companies could use it to optimize routes and warehouses. Robotics could bring AI into factories and other physical environments, and autonomous systems could extend its use into transportation.
Tam pointed to healthcare and education as other sectors where AI adoption could create meaningful earnings improvements.
Meanwhile, Bai highlighted the importance of keeping AI costs low enough to encourage widespread adoption.
“We emphasize resource efficiency. We must make the usage of tokens cheap enough,” he said. “When many people use the AI models, Chinese companies can gather a lot of data and make their models more accurate through fast iterations.”
This could reinforce an advantage that China has been developing for years: a large domestic market provides companies with an extensive environment in which to test, refine and deploy data-intensive technologies.
What could derail the AI opportunity in China’s manufacturing sector?
There are also risks to consider.
Tam highlighted geopolitical restrictions as one potential constraint, particularly if the US imposes further restrictions on Chinese exports of AI-related hardware such as optical transceivers. In the short term, she said, this could hurt exports, although strong domestic demand could provide some offset.
Bai drew a distinction between the long-term technology cycle and the short-term financial cycle surrounding AI investment. Even if AI delivers substantial productivity gains, excessive capital expenditure or inflated valuations could create vulnerabilities along the way, he said.
Ultimately, the value of technological progress will depend on how effectively it translates into durable competitive advantages. That depends on companies’ ability to deploy AI at scale, the quality of their engineering and supply-chain capabilities, and whether adoption produces tangible improvements in costs, productivity or revenues.
China’s manufacturing ecosystem provides a strong platform for pursuing that opportunity. But the global AI landscape is still forming, and China’s role in its eventual structure — as a hardware provider, an application market, or a model developer — is still being determined.
As Huang put it: “Investors should stay flexible as this evolves.”
To learn more about China investment trends, explore these stories:
Unpacking China’s vision for its capital markets
China’s role in supplying the clean energy transition
Investing in the next phase of China’s global expansion
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