China Electrical Equipment Group's booth is seen during an expo in Zhengzhou, Henan province. MA JIAN/FOR CHINA DAILY
As global manufacturing rapidly shifts toward digitalization and intelligent development, the deep integration of artificial intelligence into the sector has become a key driving force for high-quality development and a key battleground in global tech competition, said Zhang Fan, a deputy to the National People's Congress.
Zhang, who is also director of the science and technology innovation department of China Electrical Equipment Group Co Ltd, highlighted the rapid evolution of AI technologies — including large language models, generative AI and embodied AI — saying that they are reshaping global industrial competition and integrating into various industries.
"With the rise of domestic companies like DeepSeek and Unitree Robotics, AI is being pushed toward an era of democratization, breaking the monopoly of Western tech giants and fueling rapid advancements in AI-powered devices such as smart glasses and robots," he said during an exclusive interview with China Daily.
According to this year's Government Work Report, under the AI Plus initiative, the country will work to effectively combine digital technologies with China's manufacturing and market strengths. The country will support the extensive application of large-scale AI models and vigorously develop new-generation intelligent terminals and smart manufacturing equipment.
While China has introduced policy frameworks such as the next-generation AI development plan, Zhang argued that manufacturing, spanning 41 subindustries, requires more precise and sector-specific policy implementation.
Using the electrical equipment manufacturing sector as an example, Zhang pointed out gaps in industry-level AI roadmaps, insufficient guidance for high-value applications and a lack of collaborative mechanisms for tackling common technological challenges.
"The sector needs a clear, tiered national strategy — short-term breakthroughs in foundational applications, medium-term advances in core scenarios and long-term development of a tech system."
Zhang added that a major concern is inefficiency in industry-specific AI models, saying that industrial AI training is constrained by poor data availability and limited sharing.
"Industry data, the 'fuel' for AI models, suffers from both insufficient quantity and quality," he said, citing issues such as incomplete data collection, lack of standardization and concerns over data security and commercial confidentiality.
Meanwhile, the deputy also underscored a severe shortage of interdisciplinary talent proficient in both AI and industrial processes.
"There is a disconnect between academia and industry, and traditional manufacturing companies lack structured AI talent training mechanisms."
To address the issues, Zhang said it is necessary for the nation to accelerate AI development planning for key industries.
"Given its strategic importance to energy security and China's dual-carbon goals, the electrical equipment manufacturing sector should have a dedicated AI development roadmap."
Meanwhile, he said AI innovation hubs should be formed to consolidate resources and develop industry-specific AI models that enhance efficiency and competitiveness.
More efforts should also be made to build a high-quality industrial data ecosystem. "The government should accelerate national AI data standardization, introduce tax incentives for data sharing and foster collaboration between leading enterprises to build standardized, high-value industrial datasets," Zhang added.
Li Chao, chief economist at Zheshang Securities, said AI — in which the United States and China are seeking to gain a competitive edge — is poised to see accelerated development in the future.
