China on AI Job Loss: “No ‘Matrix’ for us, thanks.”
“We’re a people’s republic after all.”
“Stephen G.” is a UPenn graduate who studied East Asian Languages and Civilizations. He was also a Reischauer Scholar through SPICE, Stanford University.
“Humans will be completely freed from work in the end, which might sound good but will actually shake society to its core… you could even say the mark of success for this AI revolution is that it replaces the vast majority of human jobs.” This is the warning given by a DeepSeek spokesperson at the World Internet Conference in Wuzhen 乌镇 in November 2025. He called on AI companies to alert the public regarding which jobs could be eliminated first. While the risk of job loss looms large around the world, China faces unique challenges due to domestic economic headwinds coupled with high expectations for AI.
The Chinese State Council published its ambitious “AI+” initiative in August, aiming to have AI devices, agents, and applications reach a penetration rate above 70 percent across society by 2027 and 90 percent by 2030. Beijing wants AI to serve as a new engine of economic growth and productivity increases. But how will China navigate the challenges of adopting AI while softening its impact on the job market? As China marches toward an AI-powered future, what strategies could policymakers develop to uphold the social contract between the party and the people?
China’s Labor Market
Since the pandemic, China’s youth unemployment rate has stayed high; in mid-2023, it reached a historical high point of 21.3%, nearly double the pre-pandemic rate in 2019, prompting the National Bureau of Statistics to suspend publication of the data. Reporting only resumed several months later using different metrics. However, joblessness data under the new metrics reached another record of 18.9% in August 2025 for “unemployed youth aged 16-24 who are not in school ” — and many believe the true figure to be much higher.
Besides, a vast number of low-skilled workers have lost stable sources of income and now rely on the gig economy. According to RAND, hundreds of millions of rural workers have become unemployed due to the housing-market collapse and the contraction of low-skilled manufacturing. Many of them now drive for ride-hailing or delivery apps, which offer little financial security or potential for upward mobility.
Defending Humans
While US coverage of AI-displacement often tends toward pessimism rather than workable solutions, the Chinese government has taken action on the issue — to an extent. In a December 2025 employment arbitration case, the Beijing Municipal Bureau of Human Resources and Social Security 北京市人力资源和社会保障局 stated that “AI replacing the job function” is not a legally valid reason for employee termination. The case involves a tech company that eliminated an employee’s position due to AI, framing automation as “a material change in the objective circumstances since the labor contract was signed 劳动合同订立时所依据的客观情况发生重大变化”. Nonetheless, the arbitrator ruled the termination unlawful, noting that a “material change” must be unforeseeable and caused by force majeure events such as natural disasters and policy changes. In contrast, the company’s adoption of AI technology was a voluntary business decision. As a result, the company was ordered to pay ¥791,815 ($113,956) in compensation for unlawful termination.
In China, employment arbitration cases typically reference precedents set by the local high court, the labor arbitration committee, and the Bureau of Human Resources and Social Security. According to a Beijing-based lawyer, this arbitration case will serve as a reference locally and could influence arbitration decisions in other provinces, especially in northern regions.
The Beijing arbitration authority further noted that under such circumstances, employers should first consider contract modifications, retraining programs, or internal transfers to accommodate affected employees. Multiple state media outlets covered the case, describing it as “setting a new benchmark 具有标杆意义” and “giving workers peace of mind 给广大劳动者吃了一颗定心丸.” Against a backdrop of heightened public anxiety over unemployment, Beijing is signaling to private-sector employers that they cannot use AI adoption as a legal justification for layoffs. But even with restrictions on layoffs, firms often circumvent statutory protections through attrition, short-term contracts, and labor dispatch arrangements. The ruling’s practical impact therefore remains uncertain, given the historically questionable enforcement of labor laws in China.
Online commentaries also raised doubts on whether the ruling will meaningfully protect workers going forward. On Zhihu, many users argue that the case is yet another example of companies pursuing layoffs without paying severance. Since most employees would not pursue the tedious arbitration process, in part due to the fear of harming future job prospects once they have an arbitration record, employers face little risk — the worst case would be paying the severances that the employee deserves initially. Multiple follow-up comments lament the absence of more punitive measures for employers in Chinese labor law.
While their implementation may fall short, more laws and regulations on AI automation can be expected. On Jan 27th, 2026, the Ministry of Human Resources and Social Security has announced that China will issue official documents to respond to the impact of AI on employment. The November 2025 issue of Study Times 学习时报, an official newspaper of The Central Party School 中共中央党校 (where elite CCP cadres get trained), also discussed legislation to manage job displacement. It recognizes that the trend of AI automation eliminating jobs has been accelerating, and that China’s current laws and regulations need to catch up.
One can look at previous evidence to gauge how such legislative efforts may unfold. Public opinion on matters regarding labor conditions has swayed the Chinese government’s regulatory response before: In September 2020, an investigative article by Renwu 人物 sparked public outrage for the plight of delivery drivers, which prompted state media to criticize the delivery platforms. Policy response came during the summer of 2021 with two new regulations on algorithms. The first required the platforms to adopt a “moderate algorithm 算法取中” that loosens up time limits on delivery, instead of the “strictest algorithm” that had forced drivers to break traffic rules in order to be “on time”. It also emphasized that drivers’ earnings must not fall below the minimum wage. The second, issued as part of a broader regulation governing internet platforms’ recommendation algorithms, mandated that companies file detailed algorithm disclosures.
The process through which China produced regulations on AI-systems themselves — including recommendation algorithms, deepfakes, and generative AI-outputs — could also help us predict how the state might respond to AI-led job displacement. Matt Sheehan of the Carnegie Endowment for International Peace reverse-engineers China’s AI regulatory development and outlines a four-layered policy process: real-world conditions; Xi Jinping and CCP ideological framing; the “world of ideas”, consisting of think tank scholars, AI scientists, and corporate lobbyists, etc.; and finally, the party and state bureaucracies. To date, much of the regulatory design has occurred within the latter two layers.
Applying this framework to workforce disruption, expect that labor-market shifts will be framed as a priority issue since they are core to Chinese social stability and common prosperity. Then the issue would command policy debate: journalists may spotlight the plight of workers displaced by automation, while corporate actors emphasize productivity gains and global competitiveness. Sheehan observes that AI-system governance currently allows relatively wide space for policy debates, in part because the field is new and competition among bureaucracies has yet to solidify.
A similar dynamic could shape regulatory responses to AI-induced displacement, allowing for more input from think tanks, media, and businesses. Although China has extensive experience managing unemployment, AI-related disruption may differ in its pace, scale, and breadth of sectors affected. This distinction may prompt policymakers to treat AI-driven job loss not merely as cyclical unemployment, but as a structural governance challenge.
Potential upcoming policy initiatives highlight the state’s plans to protect people’s livelihoods while technology rapidly advances. Study Times emphasizes that industries should adopt new technology in “human-machine coordination 人机协同” and “scientifically adjust the level of automation to materially improve employment stability 科学调节制造业自动化程度.” In the AI+ plan, the term “human-machine coordination人机协同” also appears in the first paragraph. The term has been defined as “the process of humans and intelligent systems (including algorithms, artificial intelligence and robots) completing tasks together”.
This concept has been further interpreted and is being put into practice. Cai Fang 蔡昉, a prominent Chinese economist and president of the Labor Economics Society 劳动经济学会会长, argues that AI should be guided by policies that prioritize human-machine collaboration over efficiency gains from automation alone. Some current AI applications in China reflect this awareness. For example, robots from Unitree have become “AI Physician Assistants”, making clinical rounds as part of a “human-machine-coordination multidisciplinary team (MDT) 人机协同MDT” at Fuzhou University Affiliated Provincial Hospital 福州大学附属省立医院. Unlike Silicon Valley companies bragging about being “fully AI native”, official directives in China often prominently display human involvement and show a clear intention to manage AI’s threat to the workforce.
Proposals and Challenges
Proposals addressing AI-driven labor concerns are abundant in China. During the 2025 Two Sessions meeting, Liu Qingfeng 刘庆峰, the CEO of iFLYTEK 科大讯飞 and an NPC (National People’s Congress, which generally rubber-stamps decisions already made at the highest levels of the CCP) deputy, suggested “AI-specific unemployment insurance AI失业保障专项保险”, a 6-12-month grace period for layoffs, and more job-oriented curriculum at universities and trade schools. For low-income communities, he emphasized that the state should provide free upskilling. He also recommended building a “‘monitor, alert and respond’ system that dynamically tracks employment status 就业监测-预警-响应”全链条监测机制”, with pilot rollouts in the Yangtze and Pearl River Deltas. The platform would require businesses with extensive AI-usage to provide data on job replacement to predict unemployment risks.
During the Two Sessions, Guoquan Lü 吕国泉, the All-China Federation of Trade Unions chief of staff, also highlighted practices in Spain, Korea, and Japan that China could adopt, such as limiting enterprises from replacing more than 30% of workers in a single position, requiring a portion of automation-driven cost savings to be allocated to employee upskilling, and levying additional taxes ranging from 0.5% to 3% to fund unemployment benefits. Chinese authorities could take similar measures in the near future, which would put more pressure on companies already navigating brutal competition, tariff wars, and domestic deflation.
Besides policy proposals, several structural conditions in China may soften the impact of AI-led displacement. First, the relatively low cost of labor reduces firms’ incentives to replace workers, particularly when the technology is immature. A Chinese manufacturer interviewed by Nikkei Asia states that his automated production line equipment is sitting idle due to the high start-up cost of operating them. Instead, he continues to rely on the experienced workers who can “make better clothes than what machines can do now.” Such dynamics create a buffer against rapid job loss that many Western economies do not share.
Some believe that SOEs could absorb both new graduates and workers displaced by technological changes. In China, “employment within the system 体制内工作“ — which includes positions in government agencies, public institutions such as schools and hospitals, and centrally or locally-affiliated SOEs — has long been considered an “iron rice bowl 铁饭碗” that offers exceptional job stability for both employees and society at large. Helen Qiao, a managing director and chief economist for Greater China at Bank of America, told Nikkei in December 2025 that Chinese graduates may face less AI-led disruption than their American counterparts since “SOEs will continue to shoulder some social responsibility, cushioning the impact.”
Indeed, SOEs have helped stabilize employment to an extent. Regarding youth unemployment, many localities have issued policies encouraging SOEs to recruit more college graduates, with some regions requiring that at least half of new hires in SOEs be recent graduates.
Nonetheless, “employment within the system” is unlikely to serve as an effective employment buffer under China’s current fiscal environment. Local governments are under significant financial strain — in China’s fiscal system, they bear primary responsibility for funding government agencies, public services, and local infrastructure. Yet while a large share of China’s tax revenue flows to the central government, local governments have become significantly indebted and are under huge financial pressure. Local civil servants, whose salaries come directly from the local government budget, have seen their wage promises deteriorate from “guarantee six (months of wages annually), try for eight 保六争八” to “ guarantee three, try for six 保三争六”. Similar wage arrears have affected workers ranging from SOE employees to doctors and teachers.
The policy tools for potential AI-driven displacement may no longer be viable in 2026 due to fiscal constraints by analyzing previous reforms that supported displaced coal workers. During 2016-2020, the central government committed ¥100 billion (approximately $14 billion) to support an estimated 1.3 million displaced coal workers through benefits and compensation. In the example of Wuhai 乌海, Inner Mongolia, the central government issued funds to SOEs to provide early-retirement benefits, severance packages, delayed salary payments, and other forms of support.
Local governments were expected to contribute similar sums and also took various measures to help the former coal workers find jobs. In Wuhai, the combined efforts from the central government, the city government, and the SOEs helped prevent social instability, and no petitions were reported. Local authorities also created non-coal-mining jobs by attracting new businesses, including in chemical supply chains like coke and chlor-alkali. As a result, employment in the chemical industry surpassed that in the coal-mining industry by 2020.
Compared to the Wuhai case, the government’s capacity to address AI-driven displacement today is far more constrained. With their coffers already depleted, local governments can provide few incentives to attract industries capable of bringing in new jobs, and in a world of AI disruption, it’s not totally clear what those industries would even be. (Sectors such as manufacturing, digital media, and AI development have reportedly seen the emergence of new job categories leveraging AI, but it’s an open question which positions could provide durable employment at scale.)
Therefore, many of the ambitious proposals for managing AI-led displacement may need to incorporate self-financing mechanisms rather than relying on direct government support. As deputy Lü Guoquan 吕国泉 has suggested, one potential approach would be requiring firms to reinvest a share of automation-driven cost savings into worker upskilling.
Public discourse further reflects concerns about unemployment and the administration’s capability to address it. When I spoke by phone with Wu Hong 吴宏, an advisor to the Neuroscience and Intelligent Media Institute at the Communication University of China 中国传媒大学脑科学与智能媒体研究院顾问, he told me he thinks that “macro-level pressures, rather than isolated technological advances, are stressing the economy and employment today”.
At the implementation level, online discussions expose how labor policies unfold in practice. On Zhihu, one user wrote:
“My company has to hire hundreds of new grads every year, but the business doesn’t need these people at all. Easy peasy — after a year, most either quit on their own or are laid off, and only a small fraction stay.”
Such anecdotal observations align with empirical findings. Research by a group of economists in 2023 found that government subsidies were linked with gains in employment at the time of subsidy receipt, but that these gains reversed one year later. In Ching Kwan Lee’s seminal work on Chinese labor politics, Against the Law: Labor Protests in China’s Rustbelt and Sunbelt, she argues that the violation of labor rights is a structural problem due to the national strategy of decentralized accumulation and legal authoritarianism: While local governments are responsible for developing a pro-business local political economy, the same local officials are also expected to implement labor laws issued by the central government, who sees stability as a legitimation strategy. Such tensions could weaken local government’s effort in managing AI-led job disruption since they are simultaneously incentivized to promote business efficiency.
Human-machine-coordinated Future?
AI-driven workforce disruption carries broader implications for China’s future. The pattern of displacement may differ from that in the West. In China, low-wage workers could be the most vulnerable as robots are already serving food in restaurants, delivering room service in hotels, and guiding shoppers in malls. The country’s 200 million gig workers also face mounting threats from robotaxis and delivery drones.
In contrast, in the US and other developed economies, anxiety about automation has largely centered on white-collar professionals. Major tech firms like Amazon, Microsoft, Salesforce, and IBM have dominated headlines with AI-related layoffs. Meanwhile, growing numbers of young people in the US and UK are opting for skilled trades over college, citing fears of AI replacing knowledge work. Wu Hong told me he thinks that China’s long-standing advantage of having a large pool of skilled manufacturing workers could be challenged if Western economies use AI and robotics to reshore production. He also suggests that with automation, the West may be able to replicate China’s advantage of having a robust talent base of highly skilled tech workers.
These possible trajectories add more complexity to China’s AI transition. Managing workforce adjustment is central to China’s social stability and national prosperity, and China’s proactive stance on the matter may allow it to build a concerted response system to cushion the impact of job loss. Expect stopgap measures such as new legislation and financial incentives to be introduced. Nevertheless, the harsh fiscal reality could stall many initiatives, forcing policymakers to confront difficult trade-offs between employment protection and AI-led efficiency gains.