The Truth About A Chinese AI Video Mocking Efforts To Revitalize U.S. Manufacturing

Recently, an AI-generated video aimed at the current trade war started circulating on Chinese social media, and eventually here in the U.S. It’s simple enough: Inside what appear to be the U.S. version of manufacturing sweatshops, a bunch of “schlubby Americans” (as Yahoo puts it) toil away at sewing machines or on assembly lines for smartphones. They do not look particularly happy. At the end, the screen flashes, “Make America Great Again.”

Although it’s difficult to trace the origins back to the original publisher, the video clearly struck a nerve. The reading between the lines seems to be: Hey, before you bring these jobs back to America, are you sure you want them? Is this the future you envision for yourself?

The AI video plays on the conception that Chinese manufacturing is dark, dingy, sweaty, and low-tech. The truth is more complex.

There’s no question that in China, wages are significantly lower. As of 2022, the average manufacturing worker there makes 97,528 yuan yearly, or a little more than $13,000, according to China’s National Bureau of Statistics. Contrast that to the U.S., where the average sits around $52,000 a year, with room to grow into six-figure territory. It’s the delta between these two numbers that sent 2.8 million manufacturing jobs out of the U.S. in less than two decades.

Indeed, many of the jobs that left were lower skill and repetitive. Today, The U.S. ranks first among major economies in value added per manufacturing employee, at $141,000, according to the Cato Institute. That’s nearly seven times that of workers in China. Still, with the Chinese government’s aggressive investments, a flourishing industry there has taken root. China’s financial support for manufacturing equaled at least 1.7% of GDP as of 2019 (compared to .4% in the U.S.), but it’s likely close to 5% when you take into account investment incentives and generous policy, according to the Center for Strategic and International Studies.

That money has helped Chinese manufacturers build truly advanced, state-of-the-art facilities. The industry’s adoption of robotics, for instance, far outpaces that of the U.S.: China saw some 290,000 installations in 2022, compared to 40,000 here.

There’s not a world where the U.S. can compete with Chinese labor costs. Even if tariffs balance the cost scales, it’ll take years to build up the factory capacity required to reshore all those jobs. And then we’d need to find people to fill them—a tall order when already the U.S. is forecasted to be short some 2 million manufacturing workers by 2030. We can’t fill the high-skill positions, so how are we going to fill a sudden influx of low-skill roles? That’s the dichotomy the Chinese video exposes, in many less words than I’ve used here.

It’s the higher skill jobs that we should be focusing on. Government-backed or not, manufacturers here should be aggressively investing in technology. We can’t afford to let China win on labor cost and on tech. We can instead build a high-tech manufacturing sector while showing our young workforce that their manufacturing career can look much different than the one in that AI video—that it will be high-skill and high-paying.

So, How Do We Get There?

Generally, our efforts should be falling into two main categories:

Investments in technology: Tariffs or not, manufacturers here should be investing in their tech. The barrier to entry is not as high as one might expect from the outside, and those that don’t have cash on hand can easily find willing investors. Start by equipping the shop floor with real-time data sensors, and manufacturers will soon realize just how much ROI is buried in these technologies, spurring deeper investments.

If the last five years have taught us anything, it’s that the global environment is subject to a wide range of disruption. So, whether tariffs stick around long-term or not, companies should be investing in American capacity to build resiliency into their operations. It’s true that some products will, for the foreseeable future, continue to require tedious and repetitive human work. But others in that category can be brought into the modern age and automated through the power of American innovation—and there’s money to be made in doing so.

Investments in people: The perception problem continues to rear its head in our industry. Young people don’t have a view of the industry that aligns with the current reality, so we need to do the work of educating our youth on the benefits of a career in manufacturing. As many in the industry know, manufacturing careers can be as fulfilling as they are financially rewarding. And as we make the requisite investments in technology, that will only become truer.

To be clear, even higher skill manufacturing jobs aren’t rocket science—by and large, we’ll be able to pull from the same broad pool of talent. But we must shift our approach to training and prep, and manufacturers must take an active role in the process—investing in training programs for their existing employees, leveraging partnerships with local workforce centers and colleges, and doing the work of selling young people on manufacturing before it becomes time to make a career choice.

The economics prove out over time—manufacturing’s contribution to the GDP has doubled since 1990, yet there are nearly 5 million less jobs in the industry now than there were then, according to Haver Analytics and Federal Reserve Board data. The path to sustainable growth is through technology investments that make our factories more efficient and through programs that train our workforces to work side-by-side with that technology. Over time, as our industry grows, we will gain back the jobs while growing production exponentially.

As it stands today, American manufacturing is far behind China in scale alone. That’s the reality. As we wade through the shape and impact of extended tariffs, we must also keep an eye on what we’re truly after. It’s not the future imagined by that AI video. It’s one that is much more prosperous and promising.