Tesla’s factory in Shanghai produces far more cars per worker as its plant in California. The gap reflects something unsettling about China’s broader edge in manufacturing: It has figured out how to organize production around large-scale deployment of automation, robotics and artificial intelligence. The United States has not.
Reindustrialization is one of the few economic goals that now commands bipartisan support. Successive administrations — first Joe Biden’s, now President Trump’s — have made rebuilding American manufacturing a priority. In Washington, the gap between American factories and global competitors is often explained as the product of unfair subsidies, distorted markets or other forms of cheating.
Those factors matter, as does the power of China’s political structure to command fast change from the top down. But the central challenge for the United States is not that China bends the rules. Around the world, modern manufacturing no longer resembles the mid-20th-century factory floor. Robotics, automation and A.I. now make it possible to produce more with fewer human workers, though those who remain are more skilled and better paid. Unlike China, America has failed to reckon with this reality and organize manufacturing in ways that turn its own technological strengths into comparable gains.
Washington talks about A.I. as if it lives in research labs, venture capital portfolios and data centers. China treats it as factory work. Today, A.I. is embedded into China’s efforts to accelerate automation — guiding machines, scheduling work and detecting problems in real time. China has built more than 30,000 smart factories. More than half of all new industrial robots installed worldwide in 2024 went into Chinese factories. Research from Weijian Shan, an investor and economist based in Hong Kong, has found that, from sectors ranging from steel to shipbuilding, these factories now produce more per worker than comparable U.S. plants.
The shift is visible on the shop floor. By last year, the Chinese electric vehicle company Zeekr had over 800 robots in its factory in Ningbo. The company even experimented with putting humanoid robots to work on its factory floor lifting boxes, assembling components and performing quality checks. Rather than following fixed instructions, the robots use cameras, sensors and A.I. to respond to conditions on the line, much like driver-assistance systems that adjust to traffic. That flexibility can allow them to handle variation, work safely alongside human workers and absorb routine changes that would otherwise force production to stop. These are the kind of efficiency gains that can eventually increase productivity per worker and help ease shortages of skilled labor.
These gains are not limited to experimental systems. At Midea, one of the world’s largest home appliance manufacturers, an A.I.-driven control system coordinates robots, sensors and machines at its Jingzhou plant. A company official said the system has reduced response times from hours to seconds.
Productivity gains come from multiple forms of A.I. Software can analyze camera feeds so that defects can be removed from production. Scheduling algorithms can automatically balance production, inventory and logistics — Lenovo, for example, says it has used such systems to cut production scheduling times from hours to minutes. A.I. can also analyze streams of production data in real time and highlight small inefficiencies before they slow the entire line. The technology company Xiaomi says it used smart manufacturing and over 700 robots to produce a car every 76 seconds on average in its Beijing plant.
For a decade, Beijing has pursued factory modernization as a national project, driven by all levels of the government, beyond flagship factories like Zeekr and deep into China’s manufacturing supply chains.
Provinces fund local companies developing A.I and automation technologies. Government ministries coordinate standards so that suppliers and manufacturers can share data and solutions. The government promotes programs to train workers to use these technologies. Smaller manufacturers can plug into shared, government-supported digital networks that collect production data, coordinate schedules and monitor equipment, allowing them to adopt A.I. tools without building from scratch.
On the other side of the Pacific, U.S. policy on A.I. emphasizes frontier research in A.I. and large language model development. While America leads in these fields, this focus neglects other practical areas for using A.I. and automation, leaving American manufacturers struggling to use digital tools on the factory floor. Only 18 percent of manufacturers surveyed by the Manufacturing Leadership Council said they have formal A.I. strategies for their operations; two-thirds said they were struggling to scale A.I. test projects into production.
Some American manufacturers are experimenting with similar tools. Auto manufacturers like Ford are experimenting with A.I.-enabled visual detection systems to identify defects on assembly lines. They also investing in systems that can detect equipment problems before they shut down production lines. Yet these efforts remain fragmented.
The barriers are practical rather than technological, especially for small and midsize companies. In many factories, production data is incomplete or still recorded manually, making it impossible to use digital tools that rely on continuous information. Three-quarters of manufacturers surveyed struggle to connect older machines to systems that could help them run more efficiently. And eight in 10 report shortages of workers who can use A.I.-powered manufacturing tools. More than half say the upfront cost of A.I. projects is prohibitive.
Yet the U.S. policy response to China’s rise in manufacturing targets trade flows rather than factory performance. A familiar mix of tariffs, trade investigations and restrictions on imported components and technologies looks tough but does little to close the productivity gap.
These policies actually leave American manufacturers in a bind. When they attempt to automate, they often rely on imported robotics, sensors and machinery. Yet the Trump administration has opened a national security investigation into these robotics supply chains, potentially leading to tariffs that would raise the cost of such modernizing equipment.
If the goal is to bring manufacturing back from overseas, American policymakers should focus less on protection and more on helping manufacturers deploy digital tools. That means connecting legacy equipment to digital systems so they can generate usable data. It means modernizing older plants so equipment can integrate with sensors, software and analytics. It means investing in work force training so employees can use A.I. tools. And it means federal and state governments supporting shared digital infrastructure that allows small and midsize manufacturers to adopt advanced tools.
This is what China is doing. And other advanced economies in Germany, Japan, South Korea and elsewhere are responding with similar strategies.
America has emphasized invention and breakthroughs over deployment. But sometimes, technology needs to be treated as factory work — unsexy and perhaps boring, but essential for being competitive.
Jonas Nahm, an associate professor at Johns Hopkins University, was the senior economist for industrial strategy on the White House Council of Economic Advisers during the Biden administration.
Source images by Mikroman6/Getty Images.
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