China will carry out an action to promote employment adapting to AI development, Li Zhong, vice minister of human resources and social security, said at a State Council Information Office press conference on 10 October 2026, according to Xinhua.
The action already exists on paper. It is Box 2 of the State Council’s employment plan for 2026–2030, dated 11 June 2026, which splits it into three sub-plans: creating AI jobs, finding AI job potential in traditional sectors, and helping workers change jobs. Box 2 sets no numbers.
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The key insight: As we read it, the new element on 10 October is the announcement, not the policy: the AI employment action is Box 2 of a plan the State Council published in June, and it comes with no numbers, while the same plan calls for studying a dedicated survey system to measure AI’s effect on jobs.
Xinhua’s Chinese report lists five actions Li named: the AI employment action, a “ๆ่ฝ็ งไบฎๅ็จ” training action (in our translation, skills light up the future), a migrant-worker employment action, an action to supply high-quality public employment services, and a human resources services-plus integration action.
In Xinhua’s English report, Li said China would “actively address the impact of AI and other emerging technologies on employment, promoting the responsible development of technology and bolstering quality employment.” The wording is Xinhua’s paraphrase, not a direct quotation.
The press conference was part of the SCIO’s series on starting the 15th Five-Year Plan. The SCIO page lists Li alongside Song Xin, head of the ministry’s employment promotion department, and Wu Liduo, head of its vocational capacity building department.
Two of the ten headline indicators in Box 1 of the State Council’s 2026–2030 employment plan: urban share of employment, 65.6% in 2025 to 68% in 2030, and skilled workers as a share of the employed, 30% to 35%. None of the ten indicators mentions AI.
What the Plan Already Says
The five names match boxes 2, 4, 6, 8 and 9 of the State Council’s plan for implementing the employment-first strategy in the 15th Five-Year period (Guofa [2026] No. 16), published on gov.cn on 17 June 2026.
Box 2, the AI action, has three parts. The first is an AI job-creation plan: steer innovation resources to where job-creation potential is large, cultivate new occupations, and help small firms find “ไฝๆๆฌใ่ฝป้ๅ” (in our translation, low-cost, lightweight) paths to intelligent upgrading.
The second is a plan to find AI job potential in traditional sectors, with use promoted first in posts that are short of labour or environmentally hazardous. The third supports workers changing jobs, bringing general AI knowledge and technical skills into education and training.
The plan’s text adds more. Section 2(4) calls for exploring “ไบบๆบๅๅ็ๆฐๅๅทฅไฝๅฝขๆ”, new forms of work with human-machine collaboration. Section 32 calls for an early-warning and response system for employment risks from AI applications.
Box 10 adds a mechanism to monitor and assess AI’s impact on employment, including studying the creation of a dedicated survey system, and continued tracking of AI penetration, job creation and replacement, and changing skills demand.
The Numbers Around It
The plan’s ten headline indicators in Box 1 are general, and none mentions AI. They include an urban share of employment rising from 65.6% in 2025 to 68% in 2030, and skilled workers rising from 30% to 35% of the employed.
At the press conference, figures released showed 10.52 million new urban jobs in the first nine months of 2026, 87.7% of the annual target, with surveyed urban unemployment averaging 5.2% in the first eight months, Xinhua reported.
Wu said the ministry would set up a regular mechanism for identifying new occupations, including in AI, and would formulate or revise more than 200 national occupational standards over 2026–2030, per Xinhua. Xinhua adds that 72 new occupations, including AI trainers, were introduced in the past five years, and 11 more since the start of 2026.
Xinhua’s report also gives context figures of its own: a core AI industry above 1.2 trillion yuan with more than 6,200 enterprises, and AI adoption above 80% across key industries. It cites the recruitment platform Maimai for a 789.47% year-on-year rise in new AI-related job postings on that platform from January to July.
The Structural Read
The plan treats AI on two tracks. Box 2 aims at creating and redirecting work: new occupations, AI in traditional sectors, retraining. Box 10 and Section 32 aim at measurement and risk: a mechanism to monitor AI’s impact on employment, including studying a dedicated survey system, and an early-warning system for job risks from AI applications.
The numeric targets sit elsewhere. Box 1’s indicators cover urban jobs, unemployment, skills and insurance; none mentions AI.
The ministry’s concrete steps, as Xinhua reported them, run through occupational classification: a regular mechanism for naming new occupations and more than 200 national occupational standards over 2026–2030.
Xinhua, reporting Li Zhong at the SCIO press conference (10 October 2026)
“actively address the impact of AI and other emerging technologies on employment, promoting the responsible development of technology and bolstering quality employment”
Three Implications
EMPLOYERS IN CHINA The plan names labour-short and environmentally hazardous posts as where AI use is to be promoted first, and points small firms to low-cost, lightweight upgrades.
TRAINING AND HR PROVIDERS Box 2 brings general AI knowledge and technical skills into education and training, and the plan calls for national AI application pilot bases in the human-resources field.
ANYONE TRACKING AI AND JOBS Box 10 says China will study a dedicated survey system on AI’s impact on employment, tracking job creation and replacement and changing skills demand.
The framework puts it this way: “As execution delegates, humans relocate to delegation, oversight, and integration; returns to domain expertise rise.”
As we read it, China’s plan is a state-level version of that relocation question: Box 2 targets the move into new occupations and retraining, and Box 10 sets out to measure how much work is created and replaced along the way.
New urban jobs in China, January to September 2026: 10.52 million, 87.7% of the annual target, from figures released at the 10 October press conference as Xinhua reported them. The 2025 figure, 12.67 million, is from Box 1 of the State Council plan.
What Is Not Established
We did not find a verbatim SCIO transcript of the press conference at the time of writing; Li’s words here are as Xinhua reported them. Xinhua’s Chinese report gives the five action names only.
Box 2 sets no budget, headcount or date. The only numeric targets we found in the plan’s boxes are Box 1’s general indicators and training figures in Boxes 4 and 5, none tied to AI in the text. Nothing here says how many jobs AI will create or replace in China.
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China’s new AI employment action is Box 2 of a State Council plan published in June: three sub-plans on creating AI jobs, using AI in traditional sectors and retraining workers, with no numeric targets of its own. The plan pairs it with a mechanism to measure AI’s impact on jobs.
A note on sourcing. We read the State Council’s plan in Chinese on gov.cn on 10 October 2026, including all ten of its boxes, which appear on the page as images, and Xinhua’s Chinese and English reports of the press conference. English renderings of the Chinese texts are our own translations. Li Zhong’s and Wu Liduo’s words are as Xinhua reported them; Xinhua’s context figures are Xinhua’s. Nothing here is a forecast, and nothing here is financial or investment advice.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
