This paper systematically explores the connotation, current status, challenges, and advancement pathways of the deep integration of artificial intelligence (AI) and the manufacturing industry. The study highlights that deep integration takes data as a key driving factor, leveraging new-generation information technologies such as AI to achieve multidimensional systemic integration across technology, organization, data, and value, thereby propelling the manufacturing industry toward a fundamental transformation toward high-end, intelligent, and green development. Although China has established the world's largest manufacturing system and introduced multiple national strategies to support the development of "AI + manufacturing," significant gaps remain in areas such as independent innovation in core and key technologies, the depth of technological applications, balanced development of digital infrastructure, and the supply of interdisciplinary talent. To address these challenges, this paper proposes countermeasures including strengthening scientific and technological innovation and breakthroughs in key technologies, expanding smart manufacturing application scenarios, improving digital information infrastructure, and establishing interdisciplinary talent development systems. These measures aim to drive the comprehensive and deep integration of AI and the manufacturing industry, empowering high-quality development in manufacturing and enhancing the advancement of new-quality productive forces.
X JIANG (Tue,) studied this question.