AI Turns China’s Industrial Internet Into Factory ‘Brains’
China’s industrial internet is moving beyond simply connecting machines to the network and toward systems that can think for factories, officials and executives said at the 2026 Global Industrial Internet Conference, held September 8–10 in Shenyang, Liaoning Province. The event, themed “Intelligent Transformation, Digital Conversion—AI Empowering Industry,” showcased how artificial intelligence is enabling platforms to schedule production, cut energy use, and catch defects without human intervention.
From Connectivity to Cognition
For years, industrial digitalization meant little more than linking equipment to the internet and pushing data to the cloud. According to Xinhua, the systems on display in Shenyang represent a step further: software that schedules production on its own based on orders, inventory, and equipment status. Machines are no longer merely working—they are “making decisions.”
“The industrial internet technology system centered on industrial intelligent agents is an important lever for promoting flexible manufacturing, cost reduction, and efficiency improvement,” said Lu Tingjie, a professor at Beijing University of Posts and Telecommunications, according to Xinhua.
The shift is visible on factory floors. Shenyang Machine Tool has built five unmanned flexible production lines and three “black light factories”—fully automated plants that run without workers—applying engineering AI to smart security, energy management, and equipment data collection.
“Previously it was people watching the machines; now it’s machines watching the orders,” said Wang Xianchun, a workshop section director at the company. “Previously it relied on master workers’ experience; now it relies on data to calculate—production efficiency has greatly improved.”
Robotics firm SIASUN offered another example of embodied AI. “In the past, to have a robot hold a cup, you needed to specially write a program telling it how far to extend its arm and how much force to use,” company president Zhang Jin said. “Now, the robot has ‘eyes’ and ‘touch,’ and can identify the cup’s position through visual sensing, dynamically adjusting the robotic arm’s path and grasping force.”
A National Push With Provincial Roots
The conference underscored the scale of China’s ambitions. Vice Minister of Industry and Information Technology Xie Yuansheng said the country’s industrial internet core industry exceeded 1.6 trillion yuan (roughly US$220 billion) in 2025, with more than 360 platforms wielding industry influence, according to the Minnan Net report republishing Xinhua’s account of the opening session. He said the ministry would deepen its industrial internet innovation and development project during the 15th Five-Year Plan period (2026–2030), building a “solid digital foundation” for AI-plus-manufacturing.
Liaoning Governor Wang Xinwei said the province has folded the AI and next-generation information technology cluster, along with the industrial internet supply chain, into its “2211” modernized industrial system. He pledged to accelerate the intelligent transformation and digital conversion of manufacturing and “drive the old industrial base to renewed vitality.”
That framing matters. Liaoning and the wider northeast are China’s traditional heavy-industry heartland, an area that has long faced structural economic challenges. Hosting the global conference for an eighth consecutive year reflects the region’s strategy to reinvent itself as a smart-manufacturing hub.
Local commitments followed the rhetoric. Liaoning released implementation guidelines for 11 industrial chains and signed a batch of intelligent transformation and digital conversion projects on-site. On September 9, Shenyang Industrial Investment Development Group unveiled a 10 billion yuan AI industry fund, co-managed and jointly established with CITIC Jinshi, according to PEdaily.
Where the Value Shows Up
The conference highlighted concrete gains. Wave Cloud, a nationally recognized cross-industry platform operator, launched an AI-native industrial internet platform and reported that its electromechanical pump industry model helped the Boshan pump cluster raise enterprise quality and efficiency by an average of 30 percent and pump-selection efficiency by 80 percent. Its broader “Zhiye” industrial model has incubated 15 vertical-domain models and 43 industry agent clusters.
Other examples spanned sectors. Neusoft Medical uses a remote service platform for round-the-clock monitoring, fault early warning, and remote troubleshooting of imaging equipment worldwide—transforming from selling products to selling products plus services. Tire-maker Sailun Group’s self-developed “Rubber Chain Cloud” platform links more than 3,200 suppliers, 2,000 distributors, and nearly 60,000 stores, integrating data across research, manufacturing, supply chain, and marketing.
“The ‘chain-leader guidance, platform empowerment’ model depicts the direction of China’s manufacturing transition from enterprise intelligence to ecosystem intelligence,” said Li Chunwei, director of the Shenyang service center of the National Equipment Manufacturing Digital Supply Chain Platform.
Analysis: Tacit Knowledge as the Real Prize
The most consequential idea raised at the conference concerned what AI can extract from factories themselves. Traditional industry has accumulated vast tacit knowledge—the kind held by veteran workers who know a machine’s quirks by feel. Liang Qidong, a professor at Liaoning University’s School of Economics, argued that intelligent transformation can convert the craftsmanship of master workers, real-world scenario data, and supply-chain collaboration into capabilities “that machines can learn, enterprises can use, and the industry can replicate.”
That is the deeper promise: not just automation, but the codification of expertise that would otherwise retire with the workers who hold it. It also points to a new emphasis on combining models and data—the China Academy of Information and Communications Technology used the conference to promote a “Model-Data Resonance” action aimed at developing AI models and industrial data in tandem.
Still, the vision faces familiar hurdles. Scaling pilot projects across thousands of small and mid-sized factories is costly, and the return on digital investment is rarely immediate. China’s approach—state guidance, platform leaders, and demonstration clusters—is designed to lower that barrier, but the transition from showcase projects to broad adoption remains the central test.
What to Watch
The next phase will be defined by whether the “model factories” and pilot clusters spread beyond flagship firms to the wider manufacturing base, and whether the promised AI industry fund translates into deployed capacity. With the 15th Five-Year Plan just underway and MIIT pledging to embed AI deeper into manufacturing, the “brains” of China’s factories are set to get smarter—and the contest over who supplies them is only beginning.