AI, Employment, and the Global Great Divergence: Cai Fang on the Future of China's Labor Market

Introduction: An Economist's Warning

In the early 2020s, the global economy stands at a peculiar crossroads. On one hand, the demographic dividend that has underpinned China's rise for over four decades is fading; on the other, artificial intelligence is beginning to demonstrate its potential to disrupt industries at an unprecedented pace. Public discourse largely focuses on technological marvels or market battles. But for Cai Fang, a member of the Academic Division of the Chinese Academy of Social Sciences and former vice president of the academy, the real question is more sober: when machine intelligence meets population aging, what will happen to the world's largest labor market?

In his latest book, *New Trends in China's Employment: How Artificial Intelligence Is Reshaping the Labor Market*, Cai Fang goes beyond the common debate over "which jobs will disappear" and raises a deeper structural question: when a general-purpose technology profoundly transforms labor—the core factor of production—how should the entire economic system adapt? Published by CITIC Press, this book is not a futuristic manifesto but a systematic theoretical endeavor—one that theorizes AI's impact on employment based on China's unique demographic and institutional realities.

The Overlap of the Demographic Turning Point and the AI Shock

For a long time, China's position in the global economic order has been closely tied to its population size. But that era is ending. China's working-age population has been declining for more than a decade, and the pace of aging is accelerating. In this context, AI presents a paradox: on one hand, automation and algorithmic intelligence can compensate for insufficient labor supply and support productivity growth; on the other, AI-driven substitution may hit jobs whose skills are most easily routinized—a risk that is particularly acute in China, where the social safety net and labor market institutions are still evolving.

What distinguishes Cai Fang's analysis is his insistence on urgency. AI is not a distant event; it is reshaping the labor market in real time. From ChatGPT to DeepSeek, the rapid deployment of large language models has shifted the discussion from theoretical extrapolation to practical policy challenges. The AI Action Summit held in Paris in February 2025—where 60 countries, including China, signed a declaration on inclusive and sustainable AI—shows that employment has become a global governance issue, not merely a domestic concern.

From ChatGPT to DeepSeek: The "Toyota Moment" of the Technological Path

DeepSeek, a Chinese AI startup founded in 2023, has been described by Western media as a "Sputnik moment"—a metaphor tinged with Cold War connotations, acknowledging a major technological breakthrough while also expressing concern over intensifying international AI competition. But a reader's letter to the British *Financial Times* offered a more illuminating comparison: the "Toyota moment." Toyota did not invent the automobile; rather, it reshaped the auto industry through lean, efficient production, making reliable cars accessible to billions of people. Similarly, DeepSeek's "small but refined" models reduce costs through algorithmic optimization, focus on vertical applications, and adapt to the Chinese-language context, enabling AI to be integrated into daily work and life more quickly.This distinction goes far beyond corporate strategy. The “Sputnik” narrative views AI as a zero-sum geopolitical contest, where one country’s gain necessarily comes at another’s loss. The “Toyota” narrative, by contrast, suggests that the most far-reaching AI breakthroughs may come from innovations that democratize technology—lowering costs, embedding into daily life, and creating new economic value across a wide range of industries. For a country like China, which has both the world’s largest labor force and a vast domestic market, an efficiency-driven path may matter more than a race toward general artificial intelligence. It may even enable developing economies long constrained by infrastructure and resource limitations to leapfrog into the AI era.

Historical Echoes of the Great Divergence

Cai Fang offers a sharp historical analogy. The Industrial Revolution gave rise to the “Great Divergence”—a handful of Western countries rose rapidly while much of the world fell behind. The late 20th century then saw a “Great Convergence,” driven by globalization, in which developing economies—especially China—narrowed the gap with developed countries. Now, AI may disrupt this trajectory, and the direction remains uncertain.

If AI is monopolized by a few advanced economies and large tech giants, it could deepen inequality and recreate new forms of divergence. But if AI technology becomes cheap, adaptable, and widely disseminated, it may enable developing countries to bypass the traditional stage of industrialization. In this sense, China’s choice is not merely a domestic matter. As a global leader in AI research and robot deployment, and as a country that has already lifted hundreds of millions out of poverty, whether China can successfully manage its employment transition will send a signal to the entire Global South.

Yet Cai Fang warns that the outcome is not predetermined. It depends on collective human choices—the key lies in whether policy institutions can innovate as quickly as the technology itself.

Human Capital and a New Economic Model: The Policy Crux

The book’s call for “innovation in economic models and human capital investment strategies” is not a policy slogan but a response to a hard reality: the growth model based on surplus labor and export-oriented manufacturing has exhausted its potential. The next stage of China’s modernization requires what economists call “intensive growth”—driven by productivity, skill upgrading, and creative adaptation.

Cai Fang’s emphasis on human capital should be understood in this context. It is not merely about increasing education spending, but about building a lifelong learning system that continuously updates workers’ skills in a world of accelerating automation. It also implies rethinking the social contract: how to provide income security for those disrupted by technology, and how to ensure that the gains from AI are widely shared rather than captured by a small elite. His service on the World Bank’s High-Level Commission on Jobs signals that these issues have entered the global agenda.

Moreover, the Third Plenary Session of the 20th Central Committee of the Communist Party of China has already laid out a comprehensive direction for deepening reforms. Cai Fang’s work provides an intellectual foundation for these reforms, connecting the abstract concept of “new quality productive forces” with the concrete realities of employment and social stability.

Conclusion: Choices Shape the FutureThe debate over whether AI will lead to a new round of "Great Divergence" or "Great Convergence" is not purely an academic question. It is a generational choice. For China, the challenge is twofold: it must seek global AI leadership at a time when its demographic dividend is fading. For the world, the question is whether the benefits of this technology will be contested or shared.

Cai Fang's work offers no simple answers. But it establishes a framework for thinking that rises above the noise. In an era of frequent technological breakthroughs yet scarce structural understanding, the voice of a rigorous economist with a long-term vision is increasingly indispensable. The future of employment—whether in China or globally—will be written by factors beyond algorithms: namely, the policy choices and institutional innovations that humanity makes today.