As technology advances with each passing day, artificial intelligence (AI), as the core driver of the Fourth Industrial Revolution, is reshaping the global manufacturing landscape at an unprecedented rate. Huawei's founder Ren Zhengfei's warning that "society will eventually move towards artificial intelligence, and if you don't work hard, you won't even have the opportunity to be a worker" not only reveals the inevitability of this development trend, but also puts forward urgent requirements for individuals, enterprises, and society as a whole to adapt and change. This article will discuss the use of AI in factories and the data that replaces workers from a global perspective, to support Ren's forward-looking assertion and provide insight into the socio-economic implications behind it.
In recent years, manufacturing companies around the world have embraced AI technology to improve production efficiency, product quality, resource utilization, and the ability to respond to market changes. According to the World Robotics Report 2027 released by the International Federation of Robotics (IFR), the global installation of industrial robots is expected to grow by nearly 50% between 2029 and 2030, reaching nearly 800,000 units per year. Among them, the Asian region, especially China, South Korea, Japan and other manufacturing powers, will continue to lead this growth trend.
Taking automobile manufacturing as an example, Tesla's Fremont, California factory uses a highly automated production line to integrate AI algorithms, Internet of Things technology, and collaborative robots to realize intelligent operations in body welding, painting, and final assembly. According to the company, the plant's Model 3 production line has been automated by more than 75%, significantly improving production efficiency and reducing manual errors. Similarly, the introduction of an AI-driven quality inspection system at the BMW Group in Dingolfing has been able to identify and correct small deviations in the production process in real time, reducing defect rates by nearly 30 percent.
AI technology is also widely used in equipment maintenance and supply chain management. With the help of AI prediction models, General Electric (GE) of the United States has successfully improved the fault warning accuracy of its wind power equipment to 90%, significantly reducing unplanned downtime and maintenance costs. In addition, Amazon uses AI to optimize warehouse logistics, achieve accurate inventory forecasting and automate picking, packing, and shipping processes, and it is estimated that the cost of handling every 1,000 items in its warehouse is reduced by about 20% compared with the traditional model.
In fields such as 3D printing and personalized customization, AI helps achieve on-demand production and quickly respond to market demand. Philips Medical uses AI-driven 3D printing technology to complete the design and manufacture of customized medical implants within 24 hours, shortening the cycle time by more than 90% compared with traditional processes. At the same time, the AI algorithm can also dynamically adjust the production plan to ensure that the production line can still operate efficiently in the face of high-mix, low-volume orders.
Although AI has brought about a significant increase in production efficiency, its substitution effect on traditional jobs cannot be ignored. According to research by Martin School, University of Oxford, around 47% of existing jobs worldwide are at risk of being replaced by automation within the next 20 years, with manufacturing being one of the most affected sectors.
According to the International Labour Organization (ILO), from 2015 to 2022, the share of manufacturing employment in total employment in developed countries fell by about 3 percentage points, in part due to job losses due to AI-driven automation. According to a study by PwC, by 2030, nearly 26% of working hours in China's manufacturing industry will be automated by AI, equivalent to nearly 100 million full-time jobs. However, AI will also indirectly create new jobs, such as AI system development, operation and maintenance, data analysis, etc., and it is expected that about 30% of the job losses will be offset by the new jobs.
In the face of the transformation of the manufacturing industry brought about by artificial intelligence, Ren Zhengfei's aphorism reminds us that both individuals and society need to actively respond. On the one hand, workers need to upgrade their skills and skills to work with AI and use AI tools, and move to higher value-added and more innovative career fields. On the other hand, policymakers need to reform the education system to strengthen STEM (science, technology, engineering, mathematics) education, and establish a sound social protection system to help workers who have lost their jobs due to technological progress make a smooth transition.
To sum up, Ren Zhengfei's prediction that "society will eventually move towards artificial intelligence, and there is no chance to be a worker if you don't work hard" has been vividly reflected in the process of global factory intelligence. As AI technology continues to penetrate, the manufacturing industry is undergoing profound changes, with existing jobs being replaced and new job opportunities being created. In the face of this trend, only by actively adapting, continuous learning and innovation can we find a foothold in the intelligent society and achieve win-win development for individuals and society.