What happened
At a conference hosted by China Securities Journal on August 29 in Changzhou, over 300 representatives from industry, academia, and research reached a clear consensus: artificial intelligence is shifting from a laboratory concept to a production-line reality, becoming deeply embedded in R&D, production, and supply chains.
Officials and executives highlighted Changzhou's push to accelerate AI adoption through an 'intelligent agent plus application scenario' approach, focusing on areas like industrial manufacturing, public services, and city operations. In the carbon fiber sector, Zhongjian Technology chairman Yang Yonggang stressed the need to move from selling materials to selling solutions, particularly in high-end applications such as aerospace.
Wu Zhongze, a former Ministry of Science and Technology official, said AI-manufacturing integration is advancing from single-point pilots to full-process penetration, reshaping value creation in R&D, production, quality inspection, supply chains, operations, and equipment maintenance. In biomedicine, Jiangsu Spectrum co-founder Zhang Dan noted AI's growing role in clinical trial design, preclinical models, and drug discovery optimization.
A parallel industry docking meeting brought together enterprises and financial institutions to discuss collaboration and investment opportunities in intelligent high-end equipment and AI computing infrastructure in Changzhou's New North District.
Why it matters
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Key facts
The 2026 Science and Technology Innovation and Industrial High-Quality Development Conference was held on August 29 in Changzhou, hosted by China Securities Journal, with over 300 participants.
Changzhou is building a '1028' modern industrial system with 10 advanced manufacturing clusters and 28 key industry chains, plus a '6+X' future industry layout covering AI, embodied intelligence, and synthetic biology.
Zhongjian Technology chairman Yang Yonggang said China's carbon fiber industry must shift from selling materials to selling solutions and strengthen original innovation for high-end aerospace applications.
Wu Zhongze stated that AI-manufacturing integration is moving from single-point pilots to full-process penetration, improving efficiency, reducing costs, and optimizing quality.
Zhang Dan predicted AI will see broader use in biomedicine, including clinical trial design, preclinical models, and new drug discovery optimization.
What to watch next
Watch for more concrete 'AI+' high-value scenarios to be released across manufacturing sectors, which could accelerate the shift from pilot projects to full-scale industrial adoption.
Observe whether Changzhou's dual focus on traditional manufacturing clusters and future industries like embodied intelligence and synthetic biology yields replicable models for other regions.
Keep an eye on how financial institutions will support AI infrastructure projects such as computing power buildouts, as highlighted in the docking meeting sessions.