AI adoption in Chinese enterprises boosts productivity but raises concerns over jobs and skills

Artificial intelligence is delivering substantial productivity gains in Chinese enterprises, but is also raising concerns about skills gaps, job displacement and workers’ future incomes, according to a new press release by the International Labour Organization (ILO) issued on 22 September 2026. The findings appear in a Research Brief prepared by Ekkehard Ernst of the ILO Research and Statistics Department together with researchers at Renmin University of China. The study examines how firms are adopting AI and its implications for the workforce. It concludes that AI is mainly being integrated into hybrid workflows where people continue to play an important role.

The research draws on in-depth interviews with 21 enterprises and a survey of 1,591 professionals. The firms span manufacturing, finance, business services, construction, education, media and travel. They range from an eight-person start-up to a conglomerate employing 270,000 people. Every firm interviewed was either already using AI or had concrete plans to adopt it. Among professionals surveyed, 56 per cent see AI adoption as an inevitable trend, while 47 per cent believe AI creates more jobs than it displaces, and 39 per cent expect AI to lead to declines in their income.

Significant gains, but difficult to measure

Firms that track AI’s impact report substantial productivity improvements. At one insurance company, 300 customer-service employees increased the number of issues handled each day from 6,000 to 15,000. At a large insurance group, recruitment cycle times fell from 30 days to 13 days, a 57 per cent reduction. A smart manufacturing facility reported a 30 per cent increase in production efficiency. However, most firms studied lack systematic frameworks for assessing AI’s impact beyond conventional productivity measures, and the self-reported figures have not been independently verified.

Work is changing alongside technology

Gains reported by firms are concentrated in repetitive and data-intensive tasks such as document processing, customer-query handling, résumé screening and data collection. Displacement pressures could therefore be particularly significant for routine clerical, administrative and customer-service roles. Firms also report challenges related to employee resistance, skills, AI output quality, data security, regulation and integration with existing systems. One ed-tech company identified a marked age divide in AI capabilities among employees over 40.

“Chinese firms are not replacing workers with AI so much as reorganising work around hybrid human–AI workflows,” said Ekkehard Ernst.

Skills, transitions and inclusive adoption

The brief points to four areas for policy action: strengthening AI skills and lifelong learning, particularly for mid-career and older workers; supporting workers’ transition towards higher-value tasks; developing better frameworks for measuring AI’s effects on productivity, job quality and working conditions; and helping smaller firms access AI through shared platforms, training and affordable services. These measures, the brief argues, will be important to ensure that productivity gains from AI are accompanied by decent work. They should also be distributed more broadly across workers and enterprises. Ernst noted that the real bottleneck is not the technology but the skills and management capacity to use it well. The Research Brief was published on 15 September 2026.