“The gains will be substantial”: The AI shock is looking a lot like the China shock, and a top economist says that’s actually good news

(SeaPRwire) –   In 2001, China joined the World Trade Organization, triggering a manufacturing boom. The country became known as the “world’s factory,” with its export volume increasing by 30% annually between 2001 and 2006—more than double the growth rate seen in the preceding five years.

While the U.S. benefited from cheaper imports through its new normalized trade relationship with China, the American manufacturing sector suffered: China’s production surge accounted for 59.3% of all U.S. manufacturing job losses from 2001 to 2019—approximately 4 million jobs. Economists David Autor, David Dorn, and Gordon Hanson named this phenomenon the “China shock.”

A quarter-century later, some economists have drawn comparisons between this industrial shift and today’s AI revolution. Like the China shock, AI expansion has coincided with changes in labor patterns. Although many economists find little evidence so far of widespread job displacement due to AI, tech companies have cited the technology to justify cutting thousands of positions. Last month, Snap CEO Evan Spiegel announced layoffs of around 1,000 roles, representing 16% of the company’s workforce. Klarna CEO Sebastian Siemiatkowski forecasts that AI could reduce the company’s white-collar staff by one-third by 2030.

“The AI shock is following the same playbook,” said Apollo chief economist Torsten Slok in a recent blog post. “The source of displacement is different this time—affecting cognitive and white-collar work rather than factory jobs—but every other aspect of the pattern looks strikingly similar.”

China shock vs. AI shock

According to Slok, the shared elements of labor market disruption between the AI and China shocks may not be entirely negative. After China entered the WTO, overall U.S. unemployment remained low. In fact, the manufacturing sector’s share of employment had already been declining before the China shock as the U.S. shifted toward a service-based economy.

Meanwhile, access to cheaper intermediate goods from China boosted manufacturing productivity, resulting in a 50% rise in real manufacturing value added from 2001 to 2024.

Slok observes comparable trends in productivity and labor dynamics in the AI-driven future.

“If history serves as any guide, the gains will be substantial,” he stated. “Just as lower-priced Chinese inputs enabled U.S. businesses to expand and hire more, AI is already accelerating business creation and productivity across the economy.”

Slok has previously referenced Jevons paradox to explain why AI may ultimately generate more jobs despite some companies attributing layoffs to the technology. In 1865, economist William Stanley Jevons noted that after the invention of the Watt steam engine—which improved coal engine efficiency—coal consumption actually increased significantly, as cheaper coal power encouraged greater usage.

Similarly, Slok argued in a prior blog post that as AI increases efficiency in certain white-collar tasks, demand for those roles expands, leading to net job creation. This effect can already be observed in radiology: although AI has automated portions of imaging analysis, the number of practicing radiologists in the U.S. has grown by about 10% over the past decade.

In his latest post, Slok suggested that AI could reshape job distributions across regions or generate entirely new types of employment, much like how the rise of Chinese manufacturing strengthened the U.S. service economy while enhancing productivity in manufacturing itself.

“The bottom line is that we’ve seen this before,” he concluded. “Just as the China shock led to new industries and stronger enterprises, AI will drive productivity gains and create opportunities that will more than offset current job losses.”

The case against a China shock redux

Autor, the economist who originally coined the term “China shock,” remains skeptical of the comparison. In an episode of the Possible podcast hosted by LinkedIn co-founder Reid Hoffman, he asserted that AI “will not be, in any sense, a repeat of the China trade shock.”

Unlike Slok, Autor maintains that AI will result in job displacement, but in a fundamentally different way from the China shock. He argues that AI targets specific job functions rather than entire industries or geographic areas, potentially causing broader and deeper labor transformations—without eliminating any single profession entirely.

How these labor shifts are perceived will also differ from the early 2000s, according to Autor.

“The China trade shock was viewed by U.S. firms as a purely negative competitive blow,” he explained. “Suddenly, they couldn’t maintain their pricing; another competitor was offering much lower prices. From a corporate standpoint, this was all detrimental.”

AI, however, has the potential to boost productivity and reduce costs, Autor contended—making it attractive to businesses but possibly more disruptive to workers.

“AI will be seen by many firms as a gain in productivity, which means it can still lead to worker displacement,” Autor said. “In fact, it undoubtedly will. But it will unfold very differently.”