The Moment of Truth: Chinese Algorithmic Hegemony between the “AI Plus” Plan and the Turning Point of the 15th Five-Year Plan (2026–2030)
- Gabriele Iuvinale
- 1 giorno fa
- Tempo di lettura: 6 min
Artificial Intelligence (AI) has transcended its role as a mere emerging technology to become the driving force behind a total revolution that is rewriting the rules of the game on a global scale. China is acutely aware of this, and has openly declared that AI presents a critical historical opportunity to rebuild its innovation system from the ground up and firmly establish itself as a global science and technology powerhouse. The core of this ambition is the "AI Plus" (or "AI+") Plan, a national strategy so vast and central that it mobilizes resources estimated by some sources to be around €220 billion, a figure that alone attests to the importance Beijing places on this race.
The "AI Plus" Plan is not just an economic incentive package; it is a mandate for political action operating on two fronts: injecting AI into every sector of the economy (the Industrial Integration) and simultaneously reforming the very foundations of how China produces knowledge (the Systemic Reconstruction). The ultimate goal is clear: achieving algorithmic sovereignty, making the nation completely independent of technologies and models developed in the West, especially during a time of increasing geopolitical tension with the United States.
The Breakthrough Paradigm: AI for Science and the Critical Time Window
The Chinese strategy begins with the premise that AI is reshaping the epistemology and methodology of research, accelerating the iteration of scientific theories and the restructuring of knowledge systems. China is looking ahead, projecting a trajectory that will culminate in the figure of an autonomous "AI Scientist" by 2050.
This transformation, which we are currently experiencing in its human-machine synergy phase, is altering three key aspects of knowledge:
The Structure of Knowledge. Knowledge is moving out of its disciplinary silos. AI is making knowledge more distributed, completely interconnected in a network, and borderless. It is no longer tied solely to the individual researcher or textbook, but develops in a dynamic ecosystem that links together "people, data, algorithms, and platforms". Consequently, the organization of knowledge is shifting from being rigid and "discipline-centric" (like separate chemistry or physics) to being fluid and "problem-oriented" and "task-driven".
The Process of Discovery. AI makes the knowledge creation process more autonomous, platform-based, and deeply integrated. Intelligent tools, by analyzing unimaginable amounts of data, can independently identify gaps, discover hidden patterns, and formulate new hypotheses, introducing a powerful logic of human-machine co-creation. This leads to impressive practical results:
In Life Sciences, AI promises to break the "double ten law" (ten years and ten billion dollars needed to develop a drug) , drastically reducing the time and cost of discovery, and revolutionizing the prediction of biomolecular structures.
In Materials Science, the simulation and creation of new compounds are accelerated by two or three orders of magnitude , pushing innovation along the entire "design-preparation-characterization-application" chain.
The Foundational Infrastructure: To support this revolution, the scientific infrastructure must abandon its fragmentation to become more unified, open-source, and ecological. The strategy aims to organically merge data, algorithms, computing power, and tools under a single architecture, creating an "adaptive intelligent scientific core ecosystem" essential for technological independence.
The Map of Objectives: The "AI Plus" Plan in the Real Economy
The "AI Plus" Plan translates this scientific theory into national goals that clearly demonstrate where China intends to exert its economic and social influence:
Smart Manufacturing: The goal is to bring AI into 70% of medium and large-sized enterprises by 2025. This is the backbone of the "Made in China 2025" strategy, aimed at transforming the manufacturing sector from a mass producer to a high value-added creator.
Smart Cities: China aims for 90% coverage of cities by 2030. Here, AI is used as the primary tool of governance, enabling the capillary control and optimization of urban services (from traffic management to security with facial recognition).
Digital Healthcare: With a 50% penetration target by 2025, AI is seen as a solution to address the enormous stress on the Chinese healthcare system (also due to the aging population), boosting diagnostics (e.g., in reading CT and MRI scans).
Digital Agriculture: The 25% target by 2025 focuses on creating "high-tech agricultural champions" (large state-owned farms and model cooperatives) to optimize yields and secure national food supply.
These goals are made possible by a rapid ascent in the development of entirely Chinese Large Language Models (LLMs) (homegrown). With over 1,500 AI models developed and leading players like Tencent, SenseTime, and Alibaba, China seeks not only to compete but to create an autochthonous innovation ecosystem that is insulated and resilient to external sanctions.
The Geopolitics of Computation: Strengths and Structural Vulnerabilities
The realization of the "AI Plus" Plan clashes with a complex geopolitical reality, where China's strategic advantages are measured against its inherent vulnerabilities, particularly the problem of technological dependence.
Strategic Advantages and Coordination
Research Volume. China leads globally in the total volume of articles on AI-driven scientific research. Between January 2015 and September 2025, the total number of Chinese articles reached 24,585, surpassing the United States' 22,788.
Strategic Centralization. The State Council and the Chinese Academy of Sciences (CAS) provide unparalleled coordination and alignment of resources. The "AI+ Science and Technology" action is a top priority, ensuring that funding and human capital are directed toward the transformation of the innovation paradigm.
Critical Vulnerabilities. Despite impressive progress, weaknesses threaten to curb global supremacy:
Quality vs. Quantity Gap. China lags in research influence. Highly cited articles—those containing fundamental and breakthrough innovation—are still dominated by the United States (831 against 535 for China). This gap in frontier research (deep tech) risks undermining China's ability to reach the "AI Scientist" phase.
Dependence on Advanced Computing. This is the most critical vulnerability and the geopolitical weapon of the United States. Training the largest AI models requires massive computing power (suànlì), supplied by advanced GPUs (Graphics Processing Units) produced by U.S. companies like NVIDIA. The semiconductor export restrictions imposed by the U.S. are a direct blow to Chinese computing power, slowing its frontier innovation. China is forced to focus first on exporting digital infrastructure (like the "Digital Silk Road") rather than advanced chips, as its domestic production is concentrated on more mature nodes for industrial applications.
Institutional Rigidity and Fragmentation: The rigidity of the national innovation system , based on disciplinary silos and functional blocks, is still unable to adapt to the new paradigm's fluidity. There is still significant inefficiency in computing resource use and the existence of "data silos" that obstruct the data flow necessary for AI-driven research.
The Reconstruction Imperative: Institutional and Foundational Strategy
To overcome these vulnerabilities and realize the "AI Plus" Plan, China has launched a systematic reconstruction of its national innovation system focused on four pillars:
Restructuring Disciplines and Talent Training (AI+X)
The primary goal is to break traditional disciplinary classifications to promote total convergence under the "AI+X" banner. This requires establishing interdisciplinary cluster and reforming the education system to cultivate high-level, composite "AI+" talent.
Reorganizing Actors and Integrated Collaboration
The research model must move from an isolated approach to a networked co-creation ecosystem. This entails strengthening the collaboration between National Strategic S&T Forces (like the CAS, focused on autonomous infrastructure), Universities (focused on fundamental theories), and Leading Tech Enterprises (driving rapid applications and providing data/computing power).
Consolidating Intelligent Infrastructure
To counter fragmentation and hardware dependence, the key proposal is the launch of a "National-level Scientific Foundation Model Engineering".
This project aims to build a "four-in-one" intelligent capability platform (data-algorithms-computing power-tools). In parallel, the "Intelligent Science Data Network" is planned, unifying national science data centers and promoting unified "AI-ready" data standards.
Institutional and Governance Optimization
Research management must become more flexible, involving the creation of "Intelligent Research Bodies" driven by tasks and supported by flexible teams.
It is essential to reform the research evaluation system to explicitly recognize data, models, and tools as valid research outputs , and to create incentives for the open sharing of resources.
In conclusion, China is fully aware that it is in a critical time window. The "AI Plus" Plan is the act of will to turn its quantitative strengths into qualitative supremacy and overcome dependence on Western chips. The success or failure of this systematic reconstruction will determine not only its scientific future but the entire global technological power balance for decades to come.
Commenti