As digital and intelligent technologies advance at an unprecedented pace, the digital economy has become a key engine for both expanding employment and improving job quality in China. The large-scale adoption of AI, big data, and related technologies is accelerating the transition from traditional to digital productive forces. Driven jointly by policy and technological innovation, digital intelligence is becoming deeply embedded throughout the entire industrial chain, encompassing production, circulation, and consumption. This transformation is steering employment toward more highly skilled, efficient, and resilient forms, while generating complex and far-reaching consequences for the labor market and the organization of work.

Steady expansion amid dynamic scale imbalance

New occupations are emerging in clusters and extending along entire value chains, steadily expanding the economy’s capacity to generate employment. Since China introduced its system for formally recognizing new occupations in 2019, seven batches comprising 110 occupations have been announced, with “digital,” “green,” and “livelihoods” recurring among the most prominent keywords.

Industrial digitalization is now penetrating virtually every sector. Beyond substantially improving the efficiency and competitiveness of traditional industries, it is generating a wide range of hybrid positions that combine skills once associated with separate fields. Roles are becoming more specialized, career ladders are expanding, and new positions are emerging in clusters and spreading along value chains.

Flexible employment models are evolving at the same time, bringing improvements in certain dimensions of job quality. Real-time matching powered by platform algorithms and digital contracts gives workers greater freedom to arrange when and where they work, making the balance between work and personal life more measurable, adjustable, and predictable.

Meanwhile, continued industrial upgrading is reshaping employment structures. In 2025, the “AI Plus” initiative expanded further across industries, accelerating the emergence of positions such as generative AI system testers and drone-swarm flight planners in the low-altitude economy. These new occupations are becoming important channels for attracting and employing highly skilled workers.

Transformative digital production models, however, are also creating pronounced imbalances in employment scale. Technological substitution and job creation are unfolding simultaneously, subjecting labor and employment systems to unprecedented structural growing pains. Over the long term, technological diffusion and industrial expansion can generate both job-creation and compensation effects, but these gains are distributed unevenly across regions and over time. Digital-industry hubs in eastern China are adding jobs rapidly, while traditional industrial clusters in central and western regions face accelerating losses. This countervailing pressure makes the future trajectory of employment increasingly difficult to predict and sharply narrows the window for effective policy intervention. The rise of new labor relations has meanwhile complicated broader efforts to improve job quality.

The Ninth National Survey on the Status of the Workforce found that China had 84 million workers in new forms of employment by the end of 2024, accounting for 21% of the total workforce. Their incomes fluctuate far more sharply than those of workers in traditional jobs, while algorithmic performance metrics can lock them into rigid career paths. For these workers, greater effort does not necessarily bring higher pay, and social insurance coverage may end as soon as work stops. Together, these conditions erode workers’ sense of occupational security and fulfillment, obstructing systemic improvements in employment quality. Mismatches between the supply of and demand for skills are also becoming more acute. As digital technologies accelerate industrial upgrading, the shortage of highly skilled workers continues to widen.

Improving rights protection, career development systems

Raising the overall quality of employment requires stronger labor protections alongside more robust systems for career development. The first priority should be to establish a multidimensional framework for evaluating employment quality and identifying where improvement is most urgently needed. Such a framework should cover job stability, income adequacy, reliability of protections, occupational safety, work autonomy, opportunities for skill development, social insurance coverage, and algorithmic transparency.

A second priority is to adapt the definition of rights and responsibilities to emerging forms of labor relations. Labor standards should also be established for fair remuneration, working hours, rest and leave, occupational safety, social insurance, and other provisions, providing clearer benchmarks for judicial decisions, labor arbitration, and administrative oversight.

Third, efforts should be made to chart lifelong learning and career advancement pathways in order to empower workers with sustained growth potential. At the corporate level, platform companies should establish internal systems for skill certification and promotion, convert indicators such as the quality of completed gig work and user ratings into cumulative skill credits. At the government level, authorities should accelerate the development of a national micro-credential curriculum for new occupations, build online and offline digital-skills training platforms and practical training centers, and introduce targeted capacity-building programs for key groups. These measures would lower barriers to digital learning for workers in new forms of employment and support the continuous development of vocational capabilities for all citizens.

Zhao Shuming is a senior professor of humanities and social sciences at Nanjing University and dean of the Xingzhi Academy at Nanjing University.