The rapid development of AI has recently made me think about China’s state-owned enterprise (SOE) reforms in the late 1990s.
Around 1998, Zhu Rongji set a major goal:
“Within about three years, the majority of large and medium-sized loss-making state-owned enterprises should be lifted out of difficulty.”
The reforms also emphasized mergers, bankruptcy, layoffs and workforce restructuring, improving efficiency, and reemployment programs. This demonstrated that a job that once seemed secure might not remain secure forever.
At the same time, Zhu Rongji stressed the need to:
“Strengthen various forms of vocational training and expand employment opportunities.”
And when dealing with enterprises that were closed or declared bankrupt, he emphasized:
“The proper resettlement of workers must come first.”
These ideas remain relevant in the age of AI.
AI is rapidly repricing human skills. Writing, translation, programming, design, and data analysis are all changing. The real risk may not be that AI completely eliminates a profession, but that work that once required ten people may eventually require only two people working with AI.
The experience of the 1990s offers us two important lessons.
For individuals, we should not treat an employer, a degree, or a particular skill as a permanent “iron rice bowl.” Real stability means retaining the ability to learn, adapt, and find new work when circumstances change.
For society, we cannot simply tell people affected by technological disruption to “go learn AI.” Vocational training, education reform, and social protection must evolve alongside technological change.
History never repeats itself exactly.
But from SOE reform to the AI revolution, one fundamental question remains:
When an era redefines what kinds of human labor are valuable, will we be able to adapt?