China Academy of Information and Communications Technology Jin Jian: The future industry competition is essentially AI competition, and the intelligent agent internet will become an important digital foundation

Currently, global technological innovation is entering a period of intensive activity, and China has entered a new stage where technological innovation leads comprehensive innovation. During the 14th Five-Year Plan, developing new quality productivity tailored to local conditions has been placed in an even more prominent strategic position. Future industries, as strategic battlegrounds in major power competitions, are the core tracks for forward-looking deployment of new quality productivity and for seizing the high ground in global competition. Jin Jian, Director of the Industrial Internet and Internet of Things Research Institute at China Academy of Information and Communications Technology, believes that future industry competition is essentially a competition in artificial intelligence; the key to AI competition lies in whether we can systematically organize AI innovation resources, build development paths and ecosystems for native AI models, with AI-native infrastructure such as intelligent agent internet becoming an important digital foundation to support future industry competitiveness.

Artificial intelligence is a landmark technology of the new wave of scientific revolution, the core engine driving productivity from “quantitative increase” to “qualitative leap,” and is systematically transforming production methods, industrial forms, and value creation models. It is a critical leap from “technological iteration” to “paradigm shift” in future industry competition.

Jin Jian points out that this transformation manifests in two core dimensions. On one hand, AI drives a fundamental change in scientific research paradigms. AI for Science (AI-driven scientific innovation, hereafter “AI4S”) breaks the traditional linear process of hypothesis–experiment–validation, serving not only as a research tool but also as an accelerator and amplifier of scientific knowledge production, becoming key to seizing the high ground in future industrial technological innovation. On the other hand, AI reconstructs the technological and economic characteristics and competitive logic of future industries, shifting business logic from “traffic monetization” to “value-based payment.” The competition in future industries has evolved into a comprehensive contest over development paradigms, inclusiveness, global governance discourse power, and rule-setting authority.

It is worth noting that China attaches great importance to the development of future industries. In the first year of the 14th Five-Year Plan, the Central Political Bureau held its first collective study session focused on future industry development, with artificial intelligence designated as a national strategic scientific and technological force. Various levels of government and departments have introduced a series of supporting policies, and corporate investment continues to grow. However, Jin Jian also points out that China still faces deep-rooted challenges in systematically organizing AI resources and building AI-native models, and there is an urgent need to promote deeper integration of artificial intelligence with future industries.

Specifically, first, the construction of the “three networks”—computing power network, data network, and intelligent agent network—lacks overall coordination. Issues such as limited high-end computing power, data silos, and incompatible interfaces among intelligent agent platforms are prominent, preventing these three from forming a systemic synergy and healthy cycle. Second, the potential of AI4S has not been fully unleashed; most AI applications in China are concentrated in consumer internet and traditional industry digitalization, with insufficient systematic application in basic scientific research, and a relatively lagging transformation of research paradigms. Third, development concepts and models need further deepening; some ideas still remain constrained by traditional thinking, with insufficient understanding of the essence of “AI reconfiguring production relations” in future industries and the ecological value of intelligent agent internet.

In Jin Jian’s view, artificial intelligence and future industries form the key “dual engines” for cultivating new quality productivity. Both need to work together and empower each other: AI is the core technological foundation leading industrial transformation, while future industries are the main carriers for technological implementation and value transformation. Facing strategic pressures and historical opportunities, it is necessary to be guided by the overall national security concept, adhere to both technological foundation-building and industrial breakthroughs, and systematically build new advantages for future industry competition.

Jin Jian recommends issuing a national-level special plan, establishing a national innovation system for AI4S, setting up major projects, building a scientific data sharing platform, and promoting deep AI applications in material science, life sciences, and other fields; creating demonstration zones for AI-native future industries, focusing on six major directions: future manufacturing, future information, future materials, future energy, future space, and future health, as well as frontier fields such as bio-manufacturing, quantum technology, and embodied intelligence, to develop experimental zones from “AI+” to “AI-native,” achieving full-chain intelligence in R&D, production, and operation; deepening global deployment, leveraging the Belt and Road Initiative to build a mutually beneficial international industrial ecosystem.

Advance planning and construction of the national intelligent agent internet should be prioritized, maintaining a balance between development and security, technological innovation and standardization, and steadily promoting pilot demonstrations. First, accelerate the formulation of national standards, unify communication protocols, identity authentication, security interactions, and other standards for intelligent agents, break down barriers, and enable cross-platform trusted collaboration. Second, build the infrastructure for the national intelligent agent internet, deploying public service platforms for agent registration, authentication, and scheduling, and creating standardized, reliable intelligent agent collaboration systems. Third, strengthen the construction of data networks such as “Spark Chain Network,” providing trusted data flow capabilities for cross-platform collaboration of intelligent agents, and solving core issues related to data element sharing and value circulation.