Beijing (August 29): China is aiming to achieve breakthroughs in the application of artificial intelligence (AI) in key sectors by 2027, authorities said on Friday when outlined the country's latest efforts to accelerate AI development.
At a press conference, Huo Fupeng, director of the National Development and Reform Committee (NDRC)-based innovation-led development centre, described the next year or two as a “important window” for AI deployment. He urged the mobilization of resources across society to promote advancements in six priority areas: science and technology, industry, consumption, public welfare, governance and global cooperation.
Huo's remarks came when China released a set of guidelines earlier this week to deeply implement the “AI Plus” initiative. It sets out a systematic approach to strengthening the advocacy of AI infrastructure and accelerating the integration of AI technologies across economic and social spheres.
According to Huo, the new policy document is a critical step towards fostering new quality productive capabilities and a necessary move to promote the digital economy's smart economy and transformation into an intelligent society.
The document outlines the goals for the three milestones. By 2027, the new generation of intelligent terminals and agents is expected to reach penetration rates of over 70%, and the core industry of intelligent economy will expand rapidly. By 2030, its penetration rate will exceed 90%, allowing AI to become an important economic factor. By 2035, China aims to fully enter a new phase of intellectual economy and intellectual social development.
NDRC emphasized that the latest move is just the first step. This is followed by a mix of policy tools, financial support and institutional innovation.
Zhang Kailin, deputy director of NDRC's Department of Innovation and High Tech Development, said NDRC will introduce more detailed sector-specific plans and clearer policy guidance, facilitating the development of standards to promote data sharing, model interoperability and coordinated growth of AI systems.
He also highlighted the importance of government-led investments to support AI innovation, including optimizing the distribution of computing resources to reduce R&D costs, building shared technology platforms, expanding applications in critical scenarios, and promoting the use of AI-enabled products.
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