At the opening ministerial interview of the annual NPC session on March 5, China’s industry minister Li Lecheng declared that “AI + manufacturing” is a mandatory task rather than an optional choice, and promised vigorous promotion of the initiative this year. The ministry will push firms across sectors to embrace artificial intelligence, identify and cultivate high‑value application scenarios, and develop distinctive intelligent systems tailored to industrial use.
Li framed the effort as both bottom‑up and top‑down: authorities will help firms “find scenarios” in traditional industries where AI can unlock latent productivity, while also “creating scenarios” to spur nascent and future industries. The ministry wants a portfolio of flagship applications and “characteristic intelligent agents” that demonstrate tangible gains in production efficiency, quality control, and industrial automation.
The minister stressed that the push must balance speed with safeguards. He reiterated the principle that AI should be used for human benefit, remain under human control, and be developed with security in mind. At the same time, Li called for sustained international cooperation on AI governance, seeking “open and shared” rules that could shape a broader consensus and make AI a “global public good.”
The statement sits at the intersection of two long‑running priorities for Beijing: upgrading the country’s industrial base and asserting influence over global technological governance. China has for years promoted digitalisation of factories and the creation of domestic AI ecosystems; Li’s remarks signal a renewed and more explicit campaign to weave advanced AI into manufacturing across state and private enterprises alike.
If implemented at scale, the policy could accelerate adoption of cloud computing, edge AI, robotics and model‑driven automation across sectors from heavy industry to consumer goods. That presents an opportunity to raise productivity and reduce costs, improve quality control, and shorten product cycles — outcomes Beijing needs as it seeks to move up global value chains.
But the drive also raises familiar questions. Rapid industrial deployment of AI will intensify demand for compute, chips and high‑quality data, amplifying supply‑chain pressures that have shaped recent tech policy. It may also accelerate workplace change and displacement in manufacturing regions, heightening social and retraining challenges. Finally, the call for a common governance framework is aspirational: China’s preferences on openness, data handling, and export controls will remain a point of negotiation with Western partners.
In practice, expect the ministry to follow this rhetoric with targeted measures: pilot projects, industry standards, subsidies or “scene‑finding” grants, and coordination with provincial governments and large industrial groups. For international firms and investors, the initiative widens the market for AI tools in manufacturing but also underscores the strategic importance of local partnerships, compliance with evolving standards, and the need to navigate geopolitically charged technology rules.