Expert Interview | How to Build a New Form of Intelligent Economy? Experts Analyze Its Connotation, Extension, and Development Logic

Why is the AI and Intelligent Economy called the Capability Economy, and how does it unlock new growth?

The 2026 government work report proposed “creating a new form of intelligent economy,” marking the first time this term appeared in such a report.

From the State Council’s issuance of the “New Generation Artificial Intelligence Development Plan” in 2017, to the inclusion of the “AI+” action in the 2024 government work report for the first time, and this year’s clear goal of “creating a new form of intelligent economy,” China has taken three major steps toward the intelligent era in just a few years.

Regarding the concept of “creating a new form of intelligent economy,” Chen Changsheng, deputy director of the State Council Research Office and a member of the drafting team of the government work report, explained that “we must seize the opportunities of AI development, expand the breadth and depth of AI empowering various industries, quickly open up new spaces for economic growth, cultivate new models, and strengthen new driving forces.”

How should we understand “intelligent economy”? How to “create a new form of intelligent economy”? What development logic and deeper meaning are hidden behind this new layout?

Recently, the Shanghai University of Finance and Economics Digital Economy Research Institute released a report titled “Intelligent Economy: China’s New Development Paradigm,” which states that the essence of “intelligent economy” is “capability economy,” and will profoundly reshape the global industrial competition landscape, the paradigm of national economic development, and individual capability growth paths.

The report’s author, Professor Hu Yanping of Shanghai University of Finance and Economics, recently gave an exclusive interview to The Paper (www.thepaper.cn), further analyzing and discussing topics such as “intelligent economy,” “AI development,” “industrial structure,” and “the relationship between humans and AI.”

Hu Yanping told reporters that the new form of “intelligent economy” includes not only new technologies, applications, and scenarios but also new industries and new economic development logic. It can no longer be simply summarized as a continuation of “AI+” and “digital economy.” As AI reshapes industrial economics, the process of replacing old with new also means changes in economic systems, structures, and development paradigms. The key questions are: how to develop to create incremental value to solve social problems, and how to establish new mechanisms of intelligent, inclusive, ecological, and shared development so that more people can benefit from the development of the “intelligent economy.”

【Dialogue between The Paper and Hu Yanping】

Connotation and Extension of the Intelligent Economy

The Paper: How to understand “intelligent economy”?

Hu Yanping: “Intelligent economy” is “capability economy.” Through human-developed AI, humans have unlocked the ceiling of capabilities and entered a new development channel. During the AI stage, “intelligent economy” is driven by human intelligence and smart technology together. Currently, “intelligent economy” mainly includes two parts: one is the intelligent technology industry economy, and the other is the application economy of intelligent technology. China’s goal of “creating a new form of intelligent economy” means a redefinition of development objectives, driving forces, and paradigms. “Intelligent economy” signifies that AI, technological innovation, economic factors, development logic, industry spectrum, employment, consumption, and economic cycles will fundamentally differ from the past.

The Paper: How to understand the report’s statement that the essence of “intelligent economy” is “capability economy”?

Hu Yanping: The leverage humans rely on to transform the world varies across social development stages. Initially, it was mainly physical strength, then mainly mental effort, especially knowledge and information. Now, in the AI stage, society has for the first time gained and possesses the ability to “create capabilities.” Smart technology is not only a productivity itself but also the primal force that creates productivity. Innovations in technology, business models, and new material production paradigms will emerge from this.

The Paper: What is the difference between “intelligent economy” and “digital economy”?

Hu Yanping: “Digital economy” is a broad, neutral, and flexible concept. It generally refers to economic activities where data resources are key production factors, modern information networks are important carriers, and the effective use of ICT is a major driver for efficiency and structural optimization. Essentially, the digital economy enhances productivity through information symmetry and efficiency, digitizing knowledge and information.

“Intelligent economy” is not just an extension or linear development of the digital economy but a leap in economic quality and innovation, representing a completely new economic form. Humanity’s knowledge and capabilities become models and intelligent agents, driving embodied robots or digital robots to perform more tasks and generate new productivity.

The Paper: What does “intelligent economy” mean for traditional industry economics?

Hu Yanping: AI is profoundly reshaping the form and pattern of industrial economics. From the perspective of the real economy or traditional industries, AI itself is a new industry, evolving from a technological tool to a fundamental force that reshapes traditional industries and creates new industrial economic forms. Its breadth and depth of influence, as well as its potential to spawn “AI-native” new business models, indicate that industrial economics is undergoing a systemic paradigm shift toward a new economic form, not just incremental resource optimization or efficiency improvements.

The Paper: In the long term, does this imply a restructuring of industrial structures?

Hu Yanping: The “AI+” process includes both the emergence of new industries and the exit of old industries. For individuals and industries, empowerment and impact coexist. For example, recent rapid iterations of models and intelligent agents capable of programming, writing, and image generation create both optimism and anxiety among industry practitioners. Empowerment and reshuffling are part of the necessary process to generate new industrial forms and business models. The key is how to enable all industries to share the dividends of AI development, rather than simply eliminate or replace traditional industries and workers; how to make this technological revolution more smoothly transition, more inclusively, and maintain social stability and prosperity.

The Paper: Does technological innovation mean no longer just “empowering”?

Hu Yanping: The understanding of AI for Science should not be limited to merely strengthening existing research methods. AI for Science signifies a fundamental shift in research concepts, methods, tools, organizational approaches, and even the entire research paradigm. This shift has the potential to greatly accelerate scientific discovery, achieving revolutionary breakthroughs in fields like drug development, new materials, renewable energy, and climate change—areas vital to national and public interests. This will trigger a chain reaction: humans drive technological innovation through “capabilities,” which in turn fuels industrial innovation.

Thus, the development of “intelligent economy” involves two “super cycles”: one centered on AI-driven intelligent technology industry, and another driven by AI-powered emerging and future industries. Intelligent technology provides capability foundations for new industries, and the ecological development of these industries further pushes breakthroughs in intelligent technology, creating a “flywheel effect” that elevates the economy through the interaction of these two cycles.

Development Cycles of the Intelligent Economy

The Paper: What stage is the “intelligent economy” development at now?

Hu Yanping: First, we need to understand the stages of “capability” development: capability unlocking, capability driving, and most importantly, capability creating new capabilities. The greatest significance of AI is that it can continuously produce capabilities and generate unprecedented new abilities.

The development of intelligent technology roughly goes through three stages: AI, endogenous intelligence, and autonomous intelligence. Currently, we are in the “intelligent technology industry cycle,” the late stage of the first phase. The next stage is the shift from AI to endogenous intelligence. Regarding the emerging “super cycle” driven by intelligent technology, we are still in its early phase. From a technological innovation perspective, more breakthroughs are needed, more investment is required, and it will take longer. The two cycles will start at different times but will intertwine and advance together for a considerable period.

The Paper: How do the speed of these two cycles affect social development?

Hu Yanping: China is currently facing the overlay of two “super cycles”: intelligent technology and emerging future industries.

The development of the new industries driven by intelligent technology can create more jobs and new economic forms, helping to hedge risks associated with the AI industry cycle. Additionally, leveraging the capabilities formed during the intelligent technology cycle can catalyze the overall rise of future industry clusters, allowing more social groups to participate, achieving inclusive intelligence and shared development.

When these cycles are linked via the “flywheel effect,” we may break free from existing economic cycles and enter a new development trajectory. The emerging and future industries will form large, complex modern industrial clusters. These clusters, driven by technological catalysis, innovation ecosystems, employment “sponge,” economic momentum, and strategic competition, will surpass the roles played by previous information technology industries like computers and the internet.

The Paper: What other factors should be considered in “creating a new form of intelligent economy”?

Hu Yanping: Relying solely on technology and markets, the “intelligent economy” cannot automatically complete the social closed loop, nor can intelligent technology itself sustain continuous development. The issue is not whether to develop AI but how to develop intelligent technology, for whom, and whose intelligence. On one hand, we create growth through intelligent technology; on the other, our social systems must be capable of supporting this development and managing associated risks.

Therefore, we need a clear understanding of the operation mode of the entire economic cycle under the new “intelligent economy” paradigm, and based on that, make forecasts on income distribution, employment structure changes, and other aspects for different roles, with timely market regulation. Social welfare and social security systems should also be reformed in advance—using technological guarantees as part of social security solutions—to reduce social friction during development and unleash greater social innovation potential.

The Future Relationship Between AI and Humans

The Paper: Taking embodied intelligence as an example, there is discussion that “future robots could replace humans in performing strenuous physical labor.” Does this imply two development models: “有人经济” (human-involved economy) and “无人经济” (无人 economy)?

Hu Yanping: AI can also be understood as artificial intelligence. Artificial intelligence can potentially operate independently of human intelligence, especially in interconnected systems, swarm intelligence, and superintelligence oriented toward the physical world. As artificial intelligence gradually achieves endogenous autonomy and independent action, two economic cycles—“有人经济” and “无人经济”—may emerge. This could lead to a long-term decline in human contribution as labor to economic growth, with human activity in the economy gradually decreasing. However, a reduction in humans’ proportion in economic activities does not mean a decline in human importance. In a scenario where both human-involved and autonomous AI economies coexist, the issue of human placement becomes more important than the development of AI itself.

The Paper: Recent employment market studies introduce a new indicator—“AI exposure rate,” measuring how many tasks in a profession are already covered by AI. How to understand AI’s empowerment and substitution in the workplace?

Hu Yanping: AI reduces employment, primarily affecting jobs involving intellectual labor in tech sectors like programmers and IT engineers. Recent surveys show that in professions with higher “AI exposure,” working hours tend to lengthen, and the risk of job replacement increases. Conversely, lower “AI exposure” does not necessarily mean higher future value of those professions. The mid-term employment structure depends on the expansion of new industries, the speed and scale of employment transfer, and the innovation in market systems and social welfare.

The Paper: Recently, “Lobster Farming” has become popular. How to interpret the underlying emotions?

Hu Yanping: The surge in “OpenClaw” is the result of two “tsunamis” colliding. One is the AI “tsunami,” with capabilities of AI agents advancing to the point of taking over, causing huge impacts on humans; the other is the human “tsunami,” driven by AI anxiety, the desire to learn and master AI, and the wish to enhance oneself with AI. The clash of these two “tsunamis” has created the fastest rise of AI products in history. Regardless of how we view it, the popularity of “lobster-like” products is now a fact, and they have become an ecosystem. These products are highly contested by major companies; internet firms are both “land-grabbing” and “revolutionizing themselves.” Distributed AI and open-source AI are fundamentally incompatible at the infrastructure level. For individuals, this is AI for everyone—centered on each user, connecting all AI capabilities, data resources, tools, scenarios, and workflows.

The Paper: Recently, the concept of OPC (one-person company) has also gained attention. Does this indicate that individuals skilled in AI will have advantages?

Hu Yanping: When discussing “super individuals” or “one-person companies,” we are describing a new form of human labor. Individuals mastering AI can turn intelligent agents into labor forces, managing these digital workers to perform repetitive, time-consuming tasks, potentially freeing individuals from heavy labor.

The Paper: The development of AI also prompts us to rethink “human value.”

Hu Yanping: Throughout human history, four major decouplings have occurred: humans from land, capital from production, information from space and time, and individuals from systems. After each decoupling, new relationships form dynamically. The next decoupling might be the fifth—between humans and labor.

The significance and value of humans, and self-fulfillment, are not solely tied to employment. Future individual value may depend less on repetitive labor and more on creative and collaborative abilities. Personal development could shift from a “career ladder” to a “capability network,” becoming a “super individual.” In the long run, humans and AI should develop in a complementary, dislocated manner. The goal is not to compete with machines or AI in knowledge, skills, or labor but to realize the unique value and life experience of being human. Accordingly, education should shift toward cultivating “fundamental skills,” returning focus to human qualities, fostering creativity that AI cannot replace, maintaining emotional capabilities, and moving toward holistic human development.