Why China’s AI push is fueling major ‘quiet’ layoffs

Chinese corporations are progressively shifting to quiet layoffs, marking a significant strategy where companies restructure their workforces using subtle tactics rather than resorting to massive layoffs.

The incident stems from a Hangzhou-based contractor at a prominent Chinese internet firm who said that her employer began laying off contractors in March after it directed its staff to use AI tools, including AI agent OpenClaw in China this year.

A Chinese AI agent called OpenClaw has seen lightning-fast adoption in China this year. Once these tasks are fully mapped into the system, the workers who perform them become completely interchangeable. 

Contractors are being fired, and companies have begun scaling back on entry-level hiring.

Marketing and front-end engineering jobs are the primary roles being replaced by AI across China’s big tech sector. 

While Chinese firms are trapped between two competing government goals; meanwhile Beijing demands that they adopt AI rapidly to transform economic productivity, but they must not do it so visibility that mass unemployment threatens it as “social stability.”

Most importantly, large-scale and visible layoffs carry heavy political ramifications. Consequently, private companies are actively forcing themselves to tolerate a certain level of insufficiency rather than executing massive jobs cuts in order to avoid provoking the government.

Under Chinese labor laws, any company planning job cuts that exceed 10% of its workforce must officially seek government approval first. Chinese courts have already stepped in to shield workers, ruling against companies in at least three separate legal cases where employees were dismissed purely to be replaced by AI.

According to an engineer at Alibaba’s cloud division, AI-driven reductions have officially begun. However, to avoid detection, these are happening through gradual cuts and natural attrition rather than a high-profile round of layoffs.

Some workplaces have already started measuring employee efficiency by tracking their token usage-a unit that measures AI computing consumption. 

The report underlines a major flaw in their broad performance metric noting that tracking token consumption does not translate to reliable productivity gains, nor does it reflect the actual quality of the work that a human employee produces.