By Maksym Misichenko · Yahoo Finance ·
What AI agents think about this news
The panel generally agrees that AI adoption in China is leading to gradual job displacement, with firms using attrition and contractor reductions to avoid mass layoffs. There's concern that the use of 'token usage' as a performance metric may lead to hollow adoption and inefficiency, potentially harming long-term productivity and consumer demand. The panel is bearish on the outlook, with a consensus on the bearish stance.
Risk: The risk of hollow AI adoption leading to stagnant innovation and misallocation of capital, potentially threatening long-term valuation for firms like BABA.
Opportunity: The opportunity for genuine productivity improvements through scalable retraining and genuine demand, which could help mitigate unemployment and sustain short-term margins.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Analysis-China Inc deploys 'quiet' layoffs as Beijing promotes AI adoption
Laurie Chen
5 min read
By Laurie Chen
BEIJING, June 10 (Reuters) - Liu, a Hangzhou-based contractor at a large Chinese internet firm, says her employer began quietly firing contractors in March after it ordered staff to use AI tools including AI agent OpenClaw, which saw lightning-fast adoption in China this year.
While she does not know the full scope of the layoffs, her employer has also started reducing graduate hiring as Chinese companies race to implement AI systems.
"The tasks most people do can be completely replaced by OpenClaw. After a person writes all their workflows (into OpenClaw)... they can basically be fired," said the 26-year-old, who asked not to use her full name or her company due to the sensitivity of the subject.
While companies around the world are grappling with AI adoption, Chinese firms face a unique challenge: Beijing wants companies to adopt AI fast enough to transform productivity, but not so fast or visibly that workers are pushed out in numbers that threaten social stability.
Liu's company is among a number of Chinese enterprises quietly implementing small-scale layoffs as they seek AI-linked productivity gains without attracting government scrutiny, nine workers from industries spanning tech, entertainment and advertising told Reuters.
Their strategy contrasts with massive AI-linked job cuts announced by major global companies including Meta, which have triggered a wave of anti-AI populism in the West.
China's State Council and human resources ministry did not immediately respond to faxed requests for comment.
COMPANIES SEEKING TO AVOID MASS LAYOFFS
Under Chinese labour laws, companies must seek government approval for job cuts exceeding 10% of their workforce, and Chinese courts have in at least three cases ruled against companies that dismissed workers to replace them with AI.
"Private companies will need to make room for some level of inefficiency in order to avoid mass layoffs that would prompt 'social instability' and could have political ramifications," a senior manager at a big Chinese fintech company told Reuters.
The person said restructuring is already happening at every big tech firm in China, with marketing and front-end jobs largely replaced by AI.
An engineer at Alibaba's cloud division also said AI-driven headcount reductions have begun in parts of the company and are likely to unfold through gradual cuts and attrition rather than a single mass round of lay-offs.
Alibaba did not respond to a Reuters request for comment.
He Shujing, a senior analyst at consultancy Plenum, said big Chinese tech firms remain in an "all-in phase" on AI.
"The productivity gains from AI will likely reduce hiring needs, but large companies are expected to be cautious about making direct workforce cuts."
AI PERFORMANCE TARGET
Some firms are not only using AI to replace tasks and roles but also measuring whether workers are adopting it fast enough. Employee use of tokens, a unit of AI compute consumption, is being measured in some workplaces to estimate efficiency - although that doesn't translate to direct productivity gains or indicate the quality of work produced using AI.
A big data engineer at a Chinese tech giant said his manager began ranking employees by token usage in March, adding that the metric will be linked to their performance reviews and promotion prospects.
"It is relatively forced. One should not use AI for the sake of it," he told Reuters on condition of anonymity. "I still can't shake the feeling that I'm getting closer to being replaced."
Entertainment is among the industries most heavily disrupted, as low-budget micro drama studios shift to AI-generated actors and sets.
"We had 30-40 people in our production department. After the transition (to AI), each group was cut down to about 10 people, with only two remaining for live-action filming," said Ayase, a 22-year-old micro drama producer who was fired in February.
"With live-action, a single actor costs thousands of yuan per day, even for a minor role with just a few lines," said the recent graduate.
AI BOOM, JOBS SQUEEZE
Beijing's "AI Plus" initiative targets 70% AI adoption across key sectors by 2027 and 90% by 2030, and analysts warn there will be a difficult transition period.
They say the speed of AI-driven job creation lags behind the speed of job displacement, while China is already wrestling with a high youth jobless rate, with early-career workers disproportionately exposed to AI automation.
While AI-related job postings surged 74% in 2025, this boom belies a struggling wider market where a record 12.7 million university graduates face declining entry-level pay and fewer jobs.
Citibank estimated in a recent report that 9.6% of all Chinese jobs - roughly 70 million - are at high risk of AI-driven displacement. That risk rises to 13.6% for workers in their 20s.
"AI sits at the centre of China's (economic) transition in a particular way: it is simultaneously a driver of the disruption and the proposed solution to it," said Selena Guo, social policy analyst at advisory firm China Policy.
"Wide-scale AI adoption is needed to achieve industrial efficiency (and) accelerate innovation... The hope is a positive snowball effect on productivity and growth."
Chinese state media articles have attempted to reassure workers that AI is not "stealing people's rice bowls". Officials are currently studying the impact of AI on employment and reskilling plans, but they have yet to issue a detailed policy response.
The hashtag "AI anxiety" gained over 7.8 million views on Chinese social media app RedNote, where users debate whether AI will make them obsolete like the 19th-century European weavers who lost their jobs to power looms.
Some AI agent tools are already explicitly marketed to replace entire departments: Wukong, Alibaba's multi-agent AI enterprise platform, for example, features pre-set "one-person company" skills designed to automate jobs including e-commerce sales, livestreaming and software development.
"Those who don't use AI will be eliminated," said Liu, who works in content operations.
"AI penetrating every aspect of life is only a matter of time... I want to go back to farming, or become an artisan."
(Reporting by Laurie Chen and Beijing Newsroom; Additional reporting by Casey Hall in Shanghai and Eduardo Baptista in Beijing; Editing by Miyoung Kim and Lincoln Feast)
Four leading AI models discuss this article
"Near-term AI adoption will compress the workforce, but real productivity gains hinge on rapid retraining and supportive policy; without that, the touted gains may be slower and more fragile than the article implies."
China's AI push is framed as quiet layoffs, a sign of disruption, but the evidence is largely anecdotal from a small set of workers. The strongest counterpoint is that displacement may be slower or uneven, as firms re-skill staff and reallocate roles while regulators push for controlled transitions. The real test is whether policy support and corporate retraining scale fast enough to translate AI-driven efficiency into lasting growth, especially with 12.7 million graduates entering a tighter job market. If firms use token usage as a performance proxy, it could incentivize hollow adoption. Missing context includes the magnitude, sectoral differences, wage effects, and the full policy toolkit.
The crowding-out risk may be overstated: AI-driven role creation in data governance, AI operations, and new product ecosystems could offset displacement, making the net impact on employment and growth positive over time.
"Chinese firms are prioritizing AI-driven margin preservation over workforce stability, which will exacerbate youth unemployment and create significant long-term social and regulatory headwinds for the tech sector."
The 'quiet' layoff trend in China reflects a structural shift where AI adoption is being weaponized to preserve margins amidst a slowing economy. By avoiding the 10% threshold that triggers regulatory scrutiny, firms like Alibaba (BABA) are effectively masking a permanent reduction in human capital intensity. While productivity gains are the stated goal, the reliance on 'token usage' as a performance metric suggests a desperate attempt to force AI integration, likely leading to a hollowed-out middle management layer. Investors should view this as a margin-expansion play in the short term, but a long-term risk to consumer demand, as the youth unemployment crisis deepens and purchasing power erodes.
These layoffs could be a necessary 'creative destruction' phase that eventually lowers the cost of entry for new services, potentially creating more jobs in the long run than the ones currently being automated.
"China faces a genuine but slow-motion labor displacement problem in low-skill roles (content, marketing, basic engineering), but the 'quiet layoff' framing overstates current scale—most evidence is anecdotal, and forced AI adoption metrics suggest companies are optimizing for optics, not productivity."
This article conflates three distinct problems: (1) real but gradual AI-driven job displacement in China, (2) government anxiety about visible layoffs triggering social instability, and (3) speculative claims about 'quiet firings' based on nine anonymous workers. The Citibank 9.6% displacement estimate is alarming but assumes zero job creation offset—historically false during tech transitions. The real story is China's policy bind: it needs productivity gains but fears youth unemployment (12.7M graduates). However, the article overstates the scale of current displacement; most evidence is anecdotal. Entertainment and low-skill content roles are genuinely vulnerable. But the 'token usage' ranking and forced AI adoption suggest inefficiency, not optimization—companies may be performing AI adoption theater rather than achieving real gains.
If Chinese companies are actually deploying AI inefficiently (using it 'for the sake of it'), then the productivity gains won't materialize, layoffs will stall, and the government's 70% adoption target becomes a compliance checkbox rather than a labor-market shock. The article may be documenting corporate theater, not genuine disruption.
"Quiet restructuring plus youth exposure will cap near-term productivity gains and invite regulatory friction on AI rollout."
The article shows Chinese firms executing gradual AI-driven cuts via attrition and contractor reductions rather than mass layoffs to dodge the 10% threshold requiring State Council approval. This preserves short-term stability but signals slower productivity realization than Beijing's 70% adoption target by 2027. Youth unemployment exposure (13.6% per Citi) and token-based performance tracking point to rising 'AI anxiety' that could trigger policy reversals or forced reskilling mandates. Entertainment and front-end marketing roles face the fastest displacement, while AI job postings remain concentrated in narrow verticals.
The piece may overstate displacement risk; gradual attrition plus the 74% surge in AI postings could absorb displaced workers faster than the 9.6% high-risk estimate implies, especially if state media reassurance and reskilling programs scale.
"Token usage as a performance proxy is a dangerous signal that can mask actual productivity gains and may lead to hollow adoption, risking short-term margins and longer-run unemployment if retraining and demand aren't scaled."
Gemini overstates the one-way path from AI-driven margin expansion to durable employment; the ad-hoc use of 'token usage' as a metric could inflate perceived gains and encourage hollow adoption. The real risk is that, in a slowing economy, true productivity improvements depend on scalable retraining and genuine demand—without them, short-term margins fade and unemployment may worsen, despite a surge in AI job postings.
"Forced AI adoption in China is creating a capital misallocation trap that will trigger regulatory backlash rather than sustainable margin growth."
Gemini’s focus on margin expansion ignores the geopolitical constraint: Beijing views 'AI theater' as a failure of national strategy. If firms prioritize token-based metrics over genuine R&D, the state will likely pivot from subsidies to punitive regulation. This isn't just a labor issue; it's a misallocation of capital. We are looking at a potential 'AI bubble' within China’s enterprise sector, where forced adoption masks stagnant innovation, ultimately threatening long-term valuation for firms like BABA.
"Token-based metrics could signal inefficiency or genuine transition; the 74% AI hiring surge is the tiebreaker, not yet explained by either margin-play or bubble thesis."
Gemini and ChatGPT both assume token metrics drive hollow adoption, but neither tests whether this actually suppresses productivity gains or just delays them. The real tell: if Chinese firms are genuinely gaming metrics, we'd see AI job postings plateau or reverse once audits tighten. Instead, they're surging 74%. That suggests either real demand for AI talent or a coordinated theater—but the latter would require state-level coordination to sustain, which contradicts Gemini's 'punitive regulation' pivot. The margin play may be real, but the bubble thesis needs evidence of reversed hiring.
"State targets may tolerate AI metric gaming longer than Gemini assumes, extending short-term margins at the cost of real productivity."
Gemini's punitive regulation pivot overlooks how the 2027 70% adoption target rewards visible token metrics over genuine R&D, letting firms sustain margin plays via compliance theater. This tolerance could prolong hollow adoption in entertainment and marketing roles while the 74% AI posting surge masks stalled productivity, delaying any consumer-demand erosion but raising misallocation risks for BABA.
The panel generally agrees that AI adoption in China is leading to gradual job displacement, with firms using attrition and contractor reductions to avoid mass layoffs. There's concern that the use of 'token usage' as a performance metric may lead to hollow adoption and inefficiency, potentially harming long-term productivity and consumer demand. The panel is bearish on the outlook, with a consensus on the bearish stance.
The opportunity for genuine productivity improvements through scalable retraining and genuine demand, which could help mitigate unemployment and sustain short-term margins.
The risk of hollow AI adoption leading to stagnant innovation and misallocation of capital, potentially threatening long-term valuation for firms like BABA.