Today, we are revisiting a previously well-received piece titled "An In-Depth Analysis: How Does the Nation View the Impact of AI on Employment?" in the hope that it provides you with valuable insights.
Recently, an article went viral across social media. On November 14th, an article titled "Actively Addressing the Impact of Artificial Intelligence on Employment" was published. The author is affiliated with the Economic System and Management Research Institute of the Chinese Academy of Macroeconomic Research. This institute operates under the National Development and Reform Commission and serves as a "national-level think tank department" specializing in research on economic development reforms, implementation strategies, and improvements. Many might recall that in August, the state released an action plan for "AI+". At the time, it was described as a grand blueprint for the future. This current article, however, reads more like supplementary information specifically intended for the general public. It focuses on answering several key questions of great concern: How significant is the employment impact of AI? How will the nation respond? And what preparations should we make? Understanding these issues is particularly crucial for many business owners and entrepreneurs, offering substantial guidance. Following the direction indicated by national policy could mean seizing the dividends of the era. Straying from that path might result in missing rare opportunities. Therefore, as is customary, I will dissect this article today, using the simplest language to break it down.
Official Stance: AI's Impact on Employment is Inevitable
The article begins by answering the question: Will AI actually affect your job? The national response is: Yes, and the impact will be significant. Let's look at the original text. The opening directly sets the tone, stating that the Fourth Plenary Session of the 20th Central Committee emphasized the need to improve employment impact assessment, monitoring, and early warning systems, and to comprehensively address the effects of external environmental changes and new technology development on employment. Unlike early automation, which only handled standardized tasks, generative artificial intelligence possesses cognitive abilities such as understanding and reasoning, resulting in a dual effect on employment that includes both substitution and creation. These sentences form the core of the entire article. What does this mean? "Early automation" refers to the "machines replacing humans" we understood in the past, replacing hands and feet, taking over mechanical, repetitive physical labor on assembly lines. But now, it's different. The state clearly tells us that today's "generative artificial intelligence" has developed a "brain"; it possesses cognitive abilities like "understanding and reasoning." This signifies that AI will begin replacing "mental labor." It is no longer just a robotic arm that tightens screws; it can write code, create drawings, compose articles, and even assist in decision-making. In essence, while in the past it was mainly blue-collar workers who felt insecure, in the future, more and more white-collar workers and intellectuals will also face insecurity. Regarding the final "dual effect," the state's description is "substitution" and "creation." In the future job market, AI will be the dominant force. It can both render you unemployed and create jobs for you. From these opening remarks, one might sense something unusual. Clearly, the state also feels some tension and a sense of urgency. Why this tension? The latter part of the article provides an explanation. Employment, as the foundation of people's livelihood, directly relates to economic and social stability and the nation's long-term peace and security. Therefore, scientifically assessing the dual impact of artificial intelligence on employment, tapping into its job creation potential, guarding against substitution risks, and building a precise and effective policy system have become key tasks for promoting high-quality and full employment. Simply put, the major premise for social stability and economic development is ensuring employment. With this core objective established, the next step is to clarify: Can AI truly help you get a job? And how does it make you unemployed? Only then can precise measures be formulated.
The Reality of AI: Creating Jobs and Eliminating Jobs
First, the good news: AI is indeed "creating jobs," meaning it is generating new employment opportunities. The second paragraph contains four significant signals of potential dividends. First, there is all-encompassing, industry-wide coverage. The original text states that artificial intelligence technology is reshaping the employment landscape in multiple industries such as manufacturing, finance, logistics, education, healthcare, retail, and e-commerce with unprecedented depth and breadth. In simple terms, from more physically demanding jobs like delivery, retail, and manufacturing to highly cognitive roles in finance, education, and healthcare, all are being affected by this wave of AI. Second, there is an increase in non-traditional, non-fixed employment. This section is quite detailed in the original text. On the positive side, the development of AI technology has not only led to the rapid emergence and growth of new professions within the field itself, such as algorithm engineers, data analysts, cloud computing architects, and AI product managers but has also spawned new forms and occupations like platform employment and digital labor. Furthermore, it has promoted the upgrading of traditional positions in areas like medical diagnosis and education/training, significantly enhancing production efficiency and work safety through human-machine collaboration. In essence, new employment opportunities will not only be full-time but will also include many non-full-time roles. For instance, "platform employment, digital labor, etc." can be understood in plain language as "food delivery order-taking," "crowdsourcing," "digital nomads," etc. Such work opportunities with non-fixed employment relationships are likely to become increasingly common. Third, there are state-recognized "new tracks." What are the new types of jobs? The article cites two examples: In May 2025, the Ministry of Human Resources and Social Security announced plans to add 42 new occupations, including Generative AI System Tester and Generative AI Animation Producer. Pay attention to these two new occupations: AI System Tester and AI Animation Producer. Simply put, the former can be seen as someone who specifically finds faults with AI, while the latter directs AI in creating animations. In the state's definition, this represents "human-machine collaboration." Why highlight these two specifically? This is essentially showing the cards, telling us these might currently be the most in-demand positions. Fourth, the AI talent supply-demand ratio is 1:10. At the end of this segment, the current gap is mentioned. How large is it? According to the original text, a report from the Ministry of Human Resources and Social Security shows that China's AI talent gap exceeds 5 million people, with a supply-demand ratio of 1:10. This reflects the enormous opportunities brought to the employment field by the rapid development of AI technology. A gap of over 5 million people with a 1:10 ratio means there might only be around 500,000 individuals currently qualified for AI positions, while the market needs at least 5.5 million. This indicates that the current opportunity lies in learning AI well. Whoever masters AI skills first and best is likely to benefit from this wave. However, there is always another side to the coin. The bad news is that AI's speed in "taking jobs" might be much faster than imagined. The article directly lists examples: Occupations highly exposed to AI are the first to be impacted, such as manufacturing assembly line workers, software engineers, customer service representatives, clerical assistants, junior accountants, etc., making the structural contradiction of supply-demand mismatch increasingly prominent. Note the term: "highly exposed occupations." In simple terms, these are the "jobs most easily replaced by AI." And this wave of impact has already begun. Looking at the specifics: manufacturing assembly line workers being replaced by automated equipment is something we have long been psychologically prepared for. But the subsequent ones—"software engineers, customer service representatives, clerical assistants, junior accountants, etc."—these are traditionally considered "white-collar" jobs, and most people probably aren't fully prepared. This "high-risk" list essentially states one thing: whether physical or mental labor, as long as it is standardized, repetitive, and highly substitutable, it faces potential obsolescence. Then there's the later term, "supply-demand mismatch." What does it mean? Companies want people with AI skills, but there are too many in the market with only traditional skills. This is called "supply-demand mismatch." In the AI era, this phenomenon of "people without jobs, jobs without people" will be dramatically amplified. And that's not all; a later sentence is even more pointed. The substitution effect is spreading from low-skill positions to medium- and high-skill positions. Simultaneously, the digital divide caused by uneven distribution of infrastructure and training resources further amplifies the risk of differentiation in the job market. Pay attention to that "digital divide." It suggests that whether you can use AI will determine your efficiency, income, career status, and more. To put it more bluntly, societal wealth disparity is likely to be significantly widened due to the development of AI. Viewed this way, the impact brought by AI is indeed substantial. So, are we prepared?
Current Three Major Shortcomings
Next, the article gives a very candid answer: Currently, the optimization process of China's employment system and policy framework lags behind the rapid development of artificial intelligence technology, making it difficult to proactively and effectively respond to the systemic reshaping of the employment ecosystem triggered by AI. In simpler terms: we are not prepared. And currently, there are three obvious "shortcomings." Shortcoming one: Laws have not kept pace. Consider the original text: First, the construction of relevant laws and regulations is lagging. Faced with new employment forms like platform-based work and digital labor, traditional standards for determining labor relationships have become blurred, leading to deficiencies in protecting workers' rights and interests regarding social security and occupational safety. What does this mean? Let me give an example. Suppose you take on a job training AI models online for others. The question then is: Are you considered an employee of that company? Should the company pay your social security? Are your working hours protected? Under current laws, these are difficult to define and are very ambiguous. Look at the next sentence: The widespread application of algorithm management has also raised questions about the fairness of work intensity and performance evaluation, lacking corresponding legal regulations. This might sound complex, so I'll provide some very common examples from everyday life. For food delivery, you must complete orders within the time given by the algorithm, regardless of whether you run a red light or go the wrong way; the algorithm doesn't care. For ride-hailing drivers, opening the app, you see daily required order numbers and distance quotas; whether your body can handle it, the algorithm doesn't understand. These can be termed "algorithmic exploitation." Platforms or companies use "invisible algorithms" to make you work harder, earn less, and have fewer choices, with your work completely dictated by the algorithm. In the past, we often saw these issues discussed, but many seemed to be left unresolved. This document essentially brings these matters to the forefront. In the future, regulation is imperative. Shortcoming two: Weak early warning capability. Second, there are deficiencies in the comprehensive governance mechanism for employment risks. Monitoring, assessment, early warning, and rapid response mechanisms for risks that AI may bring, such as job substitution and skill obsolescence, are not yet sound. The cross-departmental collaborative regulatory system is still incomplete, making it difficult to intervene early in structural unemployment risks. Simply put, there is currently a lack of an effective early warning system. It needs to quickly and timely know which industries AI will impact. For example, it's like AI being able to perfectly replace all translators next year, yet today we remain completely unaware. By the time that day actually arrives, countless people would suddenly become unemployed, and an entire industry could vanish. What we need is precisely such an "industry early warning system." Shortcoming three: Slow educational iteration. Third, the education and training system is out of sync with the iteration speed of AI technology. Existing educational curricula are updated slowly, and the coverage and specificity of vocational training are insufficient, leading to a supply-demand mismatch between the skill updates of workers and market demands. A lifelong learning system has not been effectively established, and learning outcomes are difficult to closely link with certification and employment. Most notably, "supply-demand mismatch" appears for the second time in the full text here. What does it mean? Companies want people proficient in AI, but schools are still teaching the old set of traditional knowledge. The result is graduates can't find jobs, and companies can't hire suitable people. So, having identified the three main current shortcomings, the next step is to address them. But how? The answer lies in the "State Council's Opinions on Deeply Implementing the 'AI+' Action" issued in August. Based on this document, the following four countermeasures were formulated.
The Nation's Four Major Countermeasures
The latter part of the article outlines four major countermeasures. For us, these are directional indicators to understand. Countermeasure one: Create new jobs. The first sentence clearly states the attitude: Stimulate the job creation effect of AI technology, and explore new growth models and points for promoting employment. In plain language, since AI's impact cannot be prevented, actively embrace it. How to embrace it? Deeply implement the "AI+" action, continuously promote and deepen the model innovation and application scenario implementation of AI technology in various fields such as industrial development, consumption quality improvement, and people's welfare. Support enterprises in using AI technology to develop new products and business formats, thereby spawning and creating new job positions. Actively guide industries to transform towards human-machine collaboration, scientifically adjust the degree of automation in manufacturing, and effectively enhance employment stability and capacity. The state will vigorously support the AI industry. It aims to integrate AI into specific scenarios like factories, shopping malls, and communities. In essence, it encourages innovation and creation. However, there is an important prerequisite: "human-machine collaboration." This means the state hopes to see AI developed, but it must not be AI alone without human involvement. The ultimate goal is for humans and machines to work together. Countermeasure two: Improve the legal system. Simply put, this means the legal system will be continuously improved in the future. However, a few sentences are particularly noteworthy for ordinary people. Avoid issues like the digital divide and algorithmic discrimination. Encourage enterprises to explore and establish more reasonable work systems in the AI era... Implement precise employment transition assistance plans, establishing unemployment assistance and re-employment aid systems tailored to different groups... I will try to summarize the two points most relevant to us: 1. Put "handcuffs" on algorithms. In the future, exploiting algorithms to oppress workers or engage in age discrimination, among other phenomena, will be prohibited. 2. Establish a safety net mechanism. If you are unfortunately replaced by AI, the state will provide subsidies and encourage you to undergo training to learn new skills. Countermeasure three: Strengthen the early warning system. Establishing an employment risk early warning system is a countermeasure specifically aimed at addressing the pain points. However, one point is particularly worth noting: Simultaneously assess the employment impact when formulating industrial policies, and pre-formulate plans for areas with high job substitution risks. What does this mean? It means that in the future, before any industrial policy is issued, an assessment must be made: Will this policy cause job losses? How many people might become unemployed? If the impact is severe, then contingency plans must be prepared in advance. This is also called "policy front-loading." Policies are set in advance to guide industries in the predetermined direction, maximizing risk prediction and minimizing losses. Countermeasure four: Reform the education system. How will education change? The two most impactful points are: 1. University majors that can be replaced by AI will be replaced. Consider this sentence: Support universities in independently optimizing disciplines and majors, opening relevant applied courses, and strengthening university-enterprise collaboration and the construction of a "dual-qualified" teaching faculty. Encourage vocational colleges and enterprises to explore various forms of cooperation, such as jointly establishing majors, courses, and internship training bases, strengthen the construction of relevant characteristic majors, and open channels for converting enterprise technical talent into vocational college lecturers. For universities, this means phasing out majors that could be replaced by AI and adding AI-related majors. For teachers, they need to be both proficient in teaching and understand real-world enterprise practices. 2. Skills may become more important than academic qualifications. Look at this sentence: Establish a nationally unified lifelong skills account, implement a "micro-certification + credit bank" system, improve the linkage mechanism between learning, certification, and employment, and help workers enhance their vocational skill levels. In the future, academic qualifications might become less important, with greater emphasis on "skills." Scenarios like this might become common: A graduate goes for a job interview, and the company might not focus on "graduating from a 985 or 211 university" but rather on whether you possess specific "AI skill certificates." How would this be verified? By opening the nationally established "credit bank," which will record every certificate you earn and every skill training session you complete. These learning achievements will be recognized by the state, much like "academic diplomas," and become hard evidence on your resume. This implies that the state is encouraging "lifelong learning." AI development is simply too fast; school textbook knowledge struggles to keep up quickly, so formal education might become more supplementary. To align with future employment, more will depend on your own initiative to learn proactively. You see, "lifelong learning" is no longer just a slogan but a means to secure your future prospects.
Final Thoughts
Having analyzed this document, what are your impressions? My feeling is one of great urgency, but also a sense of grounding. This article is officially written, and the choice of words conveys a strong sense of urgency. However, precisely because it comes from official sources, it shows us that the nation is taking action. It is pursuing technological development with one hand while ensuring a social safety net with the other. The state is openly telling us what it is doing. The state's concern is not "AI making you unemployed" but rather "your pace of transformation not keeping up with the pace of AI development." Therefore, as ordinary individuals, to seize the opportunities of the era and walk the right path, we must rely on paying attention to and interpreting these official documents. If you understand them, you can start making preparations now. Finally, I will try to share three of my thoughts with you, hoping they provide some inspiration. First, do not stand still betting that "AI is far from me." Second, do not resist the trend; instead, become part of the AI trend. Third, never stop learning; continuously evolve yourself. Your path lies at your feet. The key is to take that first step. Let's encourage each other. Best of luck.
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