For Digital China to succeed, Beijing must win what it sees as the new focal point of great power competition in the digital age: the race to design and build the world’s first nationally unified system of rules, institutions, and technology to comprehensively manage data and its intelligent application. This expresses itself in the Digital China strategy’s intense focus on the governance and control of data, a process Beijing calls the New Stage in National Informatization.

David Dorman, “Digital China: No Other Digital Strategy Is Anything Like It,” Digital China Wins the Future, June 3, 2021

Five years later, the “system” is no longer a prediction. The Digital China stack is under construction.

Distinguishing Strategy and Stack

Digital China is both a Strategy and a Stack. The Digital China strategy (a strategic framework organized by ends, ways, and means) explains how the system is used. The Digital China stack (a system architecture organized by layer) explains how the system is built. Together, they form an integrated model for understanding China’s national digital strategy.

This distinction matters because Digital China is often misread as a broad policy slogan, a digital economy strategy, or a collection of technology programs. As a national strategy, it includes all of those things, but it operates at a systems level. The Digital China stack points to that deeper structure: the national architecture through which the Party seeks to generate, circulate, apply, govern, and project digital-intelligent capability at scale.

The Digital China stack is an analytical model, but its architecture is clearly reflected in the 15th Five-Year Plan and in state-run media coverage of the Plan. A recent China Central Television report, “Charting a Clear Course for the Construction of Digital China: The 15th Five-Year Plan Centers on Data,” is a prominent example. The report summarizes and annotates the Digital China chapters of the Plan and reinforces a key point: the Party is organizing Digital China as a coordinated system of supply (compute, algorithms, data), deployment (Artificial Intelligence Plus), and governance (institutions, regulations, and international engagement).

Read through the lens of the Digital China stack, this is not simply a list of policy priorities. It is a system design.

The 15th Five-Year Plan Reveals the Stack

The CCTV report closely mirrors the Digital China chapters of the 15th Five-Year Plan. Its structure is revealing.

First, the Plan emphasizes the efficient supply of compute, algorithms, and data. This is the foundation of the system. Computing power infrastructure, model and algorithm development, and high-quality data resources are coordinated to “build a solid foundation for digital-intelligent development.”

Second, the Plan turns to system-wide deployment. Through the “Artificial Intelligence Plus”1 initiative, AI is to be integrated with scientific and technological innovation, industrial development, cultural development, public services, and social governance. The goal is not narrow AI adoption, but comprehensive empowerment across the economy, society, and the state.

Third, the Plan establishes a governance architecture for the system. It links development and regulation, strengthens Basic Systems for Data, expands AI governance, and extends Digital China outward through international cooperation in areas such as AI, digital currency, cross-border data flows, and global digital partnerships.

This sequence matters. It shows that Digital China is not being built around artificial intelligence alone. AI is the most visible frontier, but the underlying architecture is broader: compute, data, algorithms, deployment, and governance operating as one system.

The Party calls this structure “Digital-Intelligent Development,”2 a new theoretical term that integrates digitalization and intelligentization into a single process. In practice, it fuses computing power, data, and artificial intelligence across systems, processes, and industries. For the Digital China stack, Digital-Intelligent Development describes how the entire system is constructed and applied.

How the Digital China Stack Works

The Digital China stack has four functional layers operating within a cross-cutting governance layer.

At the base are the systems that support capability: a compute layer rooted in the “National Unified Computing Power Network,”3 which provides large-scale computing capacity, and a data layer anchored in the “National Data Resource System,”4 which turns data into a productive resource through systems for data sharing, public data authorization, data standards, and trusted data spaces.

Building on this foundation is the innovation layer, where compute and data are transformed into machine capability through models, algorithms, AI theory, and “Collaborative Innovation.”5 This 15th Five-Year Plan priority finds concrete form in the “Model–Chip–Cloud–Application”6 framework, which links hardware, models, platforms, and applications into a coordinated system. This is where infrastructure and data become usable intelligent capability.

Above this is the deployment layer, where those capabilities are embedded across the economy, society, and the state. “Artificial Intelligence Plus” is the clearest current expression of this layer. As a direct response to central guidance to strengthen the “AI Innovation System,”7 AI Plus is designed to move AI from labs, platforms, and models into production, public services, social governance, government administration, and everyday life.

Governance runs across the entire stack. It determines how data is owned, circulated, priced, secured, and used; how algorithms and AI systems are registered, evaluated, monitored, and regulated; and how China participates in international digital rule-setting.

The relationship between these layers is not strictly hierarchical. Compute, data, and algorithms are framed in the 15th Five-Year Plan as a coordinated system of supply. Deployment is organized through national action mechanisms. Governance shapes every layer. The stack is therefore best understood as a functional architecture: compute provides capacity; data becomes a resource; innovation turns that resource into machine capability; deployment applies that capability across national life; and governance sets the rules for how the whole system operates.

This is the larger significance of the Digital China stack. Beijing is not only trying to build better technologies. It is trying to build the system that makes technologies usable at national scale. In that sense, Digital China is a model of systems competition: the future of AI and digital power will depend not only on who has the best models, chips, or applications, but on who can organize compute, data, innovation, deployment, and governance into the most effective national architecture.

Article Roadmap

If this is your first encounter with the Digital China stack, the sections below provide a structured primer on its functional layers, and a final discussion on the national system they are creating.

Layer One: Compute

Produces computational capacity.

15th Five-Year Plan Compute System Focal Points:

  1. National Unified Computing Power Network (Primary);
  2. Compute–Green Energy Coordination;8
  3. Compute Economy;9
  4. National Unified Computing Power Monitoring and Scheduling;10
  5. Ultra-Large-Scale Intelligent Computing Clusters.11

This list is not exhaustive. It highlights five compute system focal points that are especially prominent in official documents, commentary, and reporting related to the 15th Five-Year Plan. Together, they show how the Plan conceptualizes computing power: not as an isolated technical input, but as a networked system for producing, distributing, and allocating computational capacity at national scale. The primary item reflects the clearest policy focal point; the remaining order is estimated.

The Digital China stack begins with compute because every higher layer depends on computational capacity. Data resources cannot be developed at scale without compute. Models cannot be trained, optimized, or deployed without compute. Artificial Intelligence Plus cannot move across the economy, society, and the state without compute that is accessible, affordable, and schedulable.

This is why the 15th Five-Year Plan places such emphasis on computing power infrastructure. In the CCTV summary, the Plan calls for the coordinated layout and orderly construction of computing power infrastructure; the large-scale, intensive, green, and inclusive development of compute resources; the expansion of national hub computing power infrastructure clusters; cloud-edge-end coordination; and the exploration of Ultra-Large-Scale Intelligent Computing Clusters.

The key point is organization. China is not simply building more data centers. It is trying to build a unified compute system. That system depends on national-level monitoring and scheduling, improved compute access, precision matching between supply and demand, and an independent, controllable hardware and software ecosystem.

It also depends on energy. The Plan specifically calls for the collaborative deployment of green electric power and computing power. This matters because large-scale AI and digital-intelligent transformation require not only chips and servers, but also electricity, grid coordination, cooling, and geographic planning. Compute is becoming part of China’s national infrastructure-energy system, not merely its technology system.

These developments point toward what can be understood as a Compute Economy. In this emerging system, computing power is produced, purchased, leased, scheduled, and priced as an economic resource. The Plan supports market-oriented construction and operation of computing power infrastructure, including government procurement of compute services, compute leasing, and standardized, scalable intelligent cloud services. It also emphasizes improving compute accessibility and reducing costs for small and medium-sized enterprises.

The result is a foundational layer of the Digital China stack. Compute provides the capacity on which the rest of the system depends. It is the base layer that makes large-scale data development, model innovation, AI deployment, and digital-intelligent transformation possible.

Layer Two: Data

Organizes and circulates data as a factor of production.

15th Five-Year Plan Data System Focal Points:

  1. National Data Resource System (Primary);12
  2. National Data Infrastructure;13
  3. National Unified Data Market;14
  4. National Data Resource Ledger;15
  5. Data Factor × Initiative;16

This list is not exhaustive. It highlights five data system focal points that are especially prominent in official documents, commentary, and reporting related to the 15th Five-Year Plan. Together, they show how the Plan conceptualizes data: not as an isolated resource, but as a nationally organized system for structuring, circulating, and applying data as a factor of production. The primary item reflects the clearest policy focal point; the remaining order is estimated.

If compute provides the capacity to process information, the data layer determines what that capacity can act on. This is why data sits near the foundation of the Digital China stack. Without large-scale, high-quality, usable data, computing power cannot be converted into sustained digital-intelligent capability.

The 15th Five-Year Plan places this problem at the center of Digital China. As summarized by CCTV, the Plan calls for building a National Data Resource System, improving statistical and accounting systems for data resources, and establishing a National Data Resource “Ledger.” The purpose is to make data more visible, measurable, governable, and usable across the state, public institutions, enterprises, and industries.

This is also why the Plan emphasizes data sharing, public data authorization, enterprise and industry data development, and compliance mechanisms for personal data use. The goal is not simply to collect more data. It is to move data out of fragmented silos and into controlled circulation, where it can be developed, exchanged, combined, and applied across domains.

National Data Infrastructure provides the technical and institutional foundation for that circulation. It extends the meaning of infrastructure beyond physical networks and data centers to include standards, quality management systems, trusted data spaces, data-sharing mechanisms, and systems for lawful and authorized use. The Plan also calls for AI training corpora and high-quality datasets in sectors such as energy, transportation, manufacturing, education, healthcare, and finance, showing how the data layer directly supports the innovation layer above it.

A critical part of this system is the development of a National Unified Data Market. This market is designed to make data exchangeable and allocable as an economic resource. It aims to connect data supply and demand across regions and sectors, support pricing and trading rules, and turn data from a latent asset into a usable input for production, innovation, and governance. The governance section of the CCTV report reinforces this point by calling for a national unified data market, data property-rights registration, rules for circulation and trading, and mechanisms for data pricing and revenue distribution.

The underlying problem is circulation. In Beijing’s view, data has strategic value only when it can be securely collected, standardized, authorized, exchanged, and used. That requires more than databases. It requires a national system for managing access, quality, rights, compliance, pricing, and security.

The data layer performs a central function in the Digital China stack. It turns scattered information into organized resources. It gives compute something to process, gives models something to train on, gives AI systems something to act on, and gives the Party-state a mechanism for governing digital value at national scale.

Layer Three: Innovation

Transforms data and compute into machine capability.

15th Five-Year Plan Innovation Layer Focal Points:

  1. Foundational AI Theory and Core Technologies (Primary);17
  2. Key Algorithms and Model Architectures;18
  3. Iterative Innovation in Models and Algorithms;19
  4. Collaborative Innovation;20
  5. Model–Chip–Cloud–Application.21

This list is not exhaustive. It highlights five innovation layer focal points that are especially prominent in official documents, commentary, and reporting related to the 15th Five-Year Plan. Together, they show how the Plan approaches artificial intelligence: not as an isolated technology, but as a system for producing, improving, and scaling machine capability. The primary item reflects the clearest policy focal point; the remaining order is estimated.

The innovation layer is where compute and data become usable intelligence. Compute provides processing capacity. Data provides the resource base. Models and algorithms turn both into machine capability that can be trained, optimized, evaluated, and deployed.

This is why the 15th Five-Year Plan elevates models and algorithms to foundational status. As summarized by CCTV, the Plan calls for breakthroughs in foundational AI theory and core technologies, improvements in AI model architecture, algorithm optimization, and Collaborative Innovation across “Model–Chip–Cloud–Application.”

The emphasis on Foundational AI Theory, Core Technologies, Key Algorithms, and Model Architectures reflects a larger strategic goal: self-reliance.22 Beijing does not want China to remain only a user, adapter, or deployer of imported digital technologies. It wants China to master the theories, architectures, algorithms, models, chips, platforms, and applications that define the next generation of artificial intelligence.

Equally important is the Plan’s emphasis on Iterative Innovation in Models and Algorithms. In this context, innovation is not a one-time breakthrough. It is a continuous process of training, inference, deployment, evaluation, and improvement. The CCTV report specifically highlights more efficient methods for model training and inference, the parallel development of general-purpose large models and industry-specific models, the use of high-value application scenarios to drive model deployment and upgrading, and systems for evaluating model capabilities.

This makes deployment part of the innovation cycle. Models improve through use. High-value scenarios generate feedback. Industry-specific applications create demand for better data, better compute, better architectures, and better algorithms. The result is a self-reinforcing loop: better models require more compute and data, while expanded compute and data systems make further model improvement possible.

The Plan also widens the innovation frontier beyond large language models alone. It encourages innovation in multimodal systems, intelligent agents, embodied intelligence, and swarm intelligence, while also exploring development pathways toward artificial general intelligence.

The “Model–Chip–Cloud–Application” formula captures the systemic character of this layer. It links AI models, semiconductors, cloud infrastructure, and real-world use cases into a coordinated innovation system. Algorithms are not treated as a standalone technical domain. They are developed in relation to hardware, platforms, infrastructure, data, and deployment environments.

The innovation layer performs the central conversion function in the Digital China stack. It turns compute capacity and organized data into machine capability. That capability then flows upward into the deployment layer, where AI is embedded across the economy, society, and the state.

Layer Four: Deployment

Embeds machine capability across the economy, society, and the state.

15th Five-Year Plan Deployment Layer Focal Points:

Artificial Intelligence Plus (Primary);23
Digital–Real Fusion;24
Intelligent Upgrading, Digital Transformation, and Network Connectivity;25
Digital Industry Clusters;26
National AI Innovation Highlands.27

This list is not exhaustive. It highlights five deployment layer focal points that are especially prominent in official documents, commentary, and reporting related to the 15th Five-Year Plan. Together, they show how the Plan approaches deployment: not as a scattered set of applications, but as a coordinated system for embedding digital-intelligent capability across national development. The primary item reflects the clearest policy focal point; the remaining order is estimated.

The deployment layer is where the Digital China stack becomes operational. Compute provides capacity. Data organizes resources. Innovation turns compute and data into machine capability. Deployment then embeds that capability across the economy, society, and the state.

The 15th Five-Year Plan describes this process through the language of empowerment, application, fusion, and transformation. These terms matter. They show that deployment is not simply about adopting AI tools. It is about using digital-intelligent technologies to reshape production, public services, social governance, government administration, and everyday life.

The primary mechanism is Artificial Intelligence Plus. In the CCTV summary, AI Plus is presented as a system-wide initiative to integrate artificial intelligence with scientific and technological innovation, industrial development, cultural development, public services, and social governance. Its purpose is to seize the commanding heights of AI industrial application and empower all sectors of the economy and society.

In the economy, this deployment logic appears through Digital–Real Fusion: the deep integration of the digital economy with the real economy. The Plan calls for strengthening core digital industries, developing sectors such as next-generation communications, cloud computing, and blockchain, improving high-end chips, optoelectronic devices, foundational software, and industrial software, and building globally competitive Digital Industry Clusters.

In manufacturing, the same logic takes a more operational form. The Plan emphasizes intelligent upgrading, digital transformation, and network connectivity; the Intelligent Manufacturing Initiative; the Industrial Internet Innovation and Development Initiative; and the integrated development and large-scale application of networks, identifiers, platforms, data, and security systems. This is where digital-intelligent capability is embedded directly into production systems.

The deployment layer also extends beyond industry. The Plan calls for digital-intelligent transformation in services and agriculture, digital empowerment of small and medium-sized enterprises, open-source ecosystems, smart homes, smart mobility, smart communities, AI-enabled education, healthcare, elder care, employment, consumption, and public services.

Finally, deployment reaches the state itself. The Plan calls for deeper use of digital-intelligent technologies in government services, nationwide online government platforms, cross-departmental and cross-regional data sharing, AI large-model deployment in government affairs, and AI-enabled security governance.

This is the function of the deployment layer. It translates machine capability into real-world transformation. It moves AI out of the model layer and into factories, services, communities, platforms, public administration, and security governance. In the Digital China stack, deployment is where capability becomes power.

Layer Five: Governance

Sets the rules for ownership, flow, control, and global influence.

15th Five-Year Plan Governance Layer Focal Points:

  1. National Governance Modernization (Primary);28
  2. Data Governance;29
  3. Artificial Intelligence Governance;30
  4. Regulatory and Standards Governance in the Digital-Intelligent Domain;31
  5. International Governance and Cooperation in the Digital-Intelligent Domain.32

This list is not exhaustive. It highlights five governance domains that are especially prominent in official documents, commentary, and reporting related to the 15th Five-Year Plan. Unlike the other layers of the Digital China stack, governance is not a single system. It is a cross-cutting architecture that shapes how the entire stack operates. The primary item reflects the clearest policy focal point; the remaining order is estimated.

Governance defines how data is owned, circulated, priced, secured, and used. It shapes how artificial intelligence is developed, evaluated, deployed, and controlled. It sets standards for new technologies and business models, and it extends beyond China’s borders through international digital governance, cross-border data rules, AI governance frameworks, and digital cooperation partnerships.

In this sense, governance is more than regulation. It is the control layer of the Digital China stack. It determines how digital-intelligent capability is managed, aligned with national objectives, and integrated into the functioning of the state, economy, and society.

The 15th Five-Year Plan presents this logic through the language of coordinating development and regulation. As summarized by CCTV, the Plan calls for strengthening Basic Systems for Data and artificial intelligence governance while creating a development environment that is beneficial, secure, and fair.

Data governance sits at the center of this architecture. It is anchored in the establishment and improvement of Basic Systems for Data Factors.33 The The Plan calls for systems governing data property rights, circulation and utilization, revenue distribution, and security governance. It also emphasizes a National Unified Data Market,34 data property-rights registration, rules for data circulation and trading, data pricing mechanisms, data revenue distribution, data-domain laws and regulations, and classification-based data security.

Artificial intelligence governance is a parallel domain. As machine capability becomes embedded across production, public services, social governance, and government administration, the Party is building rules to manage both innovation and risk. The Plan calls for AI laws, policy frameworks, application standards, ethical guidelines, algorithm registration, transparency management, security assessment, lifecycle risk management, monitoring, early warning, and emergency response.

Regulatory and standards governance provides the adaptive framework for technological change. The Plan calls for security regulatory frameworks for new technologies and new business models, mechanisms for developing and adjusting technology standards, tiered management of technology applications, and multi-stakeholder collaborative governance. This is how Beijing seeks to keep emerging digital systems aligned with national priorities as technology evolves.

Governance also extends outward. The Plan calls for global digital cooperation partnerships in e-commerce, digital payments, and smart cities; offshore computing power infrastructure; cross-border data flow infrastructure; participation in international governance for artificial intelligence, digital currency, and cross-border data flows; and support for AI capacity-building in Global South countries.

At the same time, governance is not only a framework for managing Digital China. It is also one of Digital China’s main deployment domains. Through Artificial Intelligence Plus, digital-intelligent technologies are being used to transform public administration, social governance, and security governance. The Plan calls for AI large models in government affairs, cross-departmental and cross-regional data sharing, intelligent government services, and AI-enabled security governance for monitoring, early warning, command decision-making, precision management, and rapid response.

This is where National Governance Modernization fits into the stack. Although the phrase does not appear as a discrete heading in the Plan’s Digital China section, the underlying pillars are present. The Plan points to Public Administration, Social Governance, and Security Governance as major domains for digital-intelligent transformation.

Public Administration Governance refers to the digital-intelligent optimization of internal bureaucracy and service delivery.35 Social Governance refers to the use of predictive technology to ensure society remains stable and manageable under Party leadership.36 Security Governance refers to the application of digital tools for early warning, precision control, and rapid response.37

Together, these domains show that Digital China is not only a technology-development architecture. It is also a state-capacity architecture. The Party is using digital-intelligent systems to reinforce its role as the central coordinator of society.

The governance layer performs the stack’s directing function. Compute produces capacity. Data organizes resources. Innovation generates machine capability. Deployment embeds that capability across national life. Governance sets the rules, controls the flows, manages the risks, and extends the system outward. It is the layer that keeps Digital China aligned with the Party’s larger objective: building a Modernized Socialist Great Power through digital-intelligent transformation.

From Strategy to System

Five years ago, the central question was whether China could translate the vision of Digital China into a coherent system. Today, that system is taking shape.

Digital China is no longer only a strategy for organizing data, computing power, artificial intelligence, and digital governance. It is becoming a model of digitalized development, both national and global. The Party seeks to demonstrate that its system can deliver efficiency, control, rising living standards, better public services, and more capable governance. The competition is therefore not only over technology. It is also over which system can most effectively translate digital capability into national transformation.

The 15th Five-Year Plan reveals the architecture of that system. Compute is being organized as nationally coordinated infrastructure for producing capacity. Data is being structured into a national system for organizing and circulating a new factor of production. Innovation transforms those inputs into machine capability through models, algorithms, and coordinated development across Model–Chip–Cloud–Application. Deployment, most visibly through Artificial Intelligence Plus, embeds that capability across the economy, society, and the state. Governance operates across every layer, setting the rules for ownership, circulation, security, risk, standards, and international influence.

Together, these layers form a national strategic system for the digital age. This is not simply a collection of technologies, or even a set of related policy initiatives. It is a unified architecture for producing, circulating, applying, governing, and exporting data-driven capability at scale.

This is where the distinction between strategy and stack matters. The stack describes the means Digital China is assembling. The strategy explains the ways those means are used to pursue broader national ends: economic transformation, governance modernization, technological self-reliance, social stability, and the construction of a globally competitive model of digitalized development.

The Digital China stack is an analytical model, but the system it describes is real. It is now being built at national scale. As it matures, Digital China offers not only an alternative model, but a potentially scalable one: a state-directed approach to organizing data, computing power, artificial intelligence, deployment mechanisms, and governance institutions into a single architecture of digital power.

That is why Digital China should be understood not only as a national strategy, but as an effort to shape the emerging global architecture of the digital age. The Party is not simply trying to win individual technology races. It is trying to build the system through which digital-era power is produced, governed, and projected.

I use AI tools to support my editing, research, and translation process. Learn more on my AI Transparency Page.

Footnotes

  1. Artificial Intelligence Plus (AI+) (人工智能+) refers to a development strategy and economic paradigm that drives industrial upgrading, process restructuring, and model innovation through the deep integration of artificial intelligence across sectors. Its core logic is analogous to that of the earlier “Internet Plus” initiative: rather than viewing AI as an isolated industry, it positions AI as a universal, foundational productivity tool that empowers traditional sectors. ↩︎
  2. Digital-Intelligent Development (数智化发展) reflects a significant shift in how Chinese policymakers understand the relationship between data and artificial intelligence. The term combines “digitalization” (the process of extracting and organizing value from data) with “intelligentization” (the use of that data to enable autonomous decision-making, learning, and innovation). Together, they express the view that data and artificial intelligence are no longer separate domains, but integrated drivers of development. English-language renderings vary; for example, some sources translate the term as “intelligent digitalization,” but the formulation “digital-intelligent development” better preserves the integrated meaning of the original. ↩︎
  3. National Unified Computing Power Network (全国一体化算力网) is China’s effort to integrate computing resources across regions, providers, and architectures into a unified, nationally coordinated system that enables computing power to be accessed and allocated on demand. It connects data centers, cloud platforms, and intelligent computing hubs through standardized interconnection and centralized scheduling, allowing compute to flow across the country much like electricity in a power grid. ↩︎
  4. National Data Resource System (国家数据资源体系) refers to a strategic framework designed to maximize the value of data as a production factor through the coordinated management, integration, and development of data assets across the entire country. It serves as a core foundation for building Digital China, aiming to transform data, currently dispersed across government, societal, and industrial sectors, into a core production factor. Despite its prominence in Chinese policy documents going back nearly a decade to the 13th Five-Year Plan for Informatization (2016–2020), the concept remains largely undeveloped in English-language analysis. ↩︎
  5. Collaborative Innovation (协同创新）is an innovation model characterized by the synergistic interaction of diverse stakeholders across the industrial chain, including government bodies and financial institutions, centered around universities, enterprises, and research institutions. ↩︎
  6. Model-Chip-Cloud-Application (模芯云用) reflects “collaborative innovation” linking artificial intelligence hardware, infrastructure, and applications. Its inclusion reinforces that algorithms are not treated as an isolated layer, but as part of an integrated technical system. ↩︎
  7. Artificial Intelligence Innovation System (人工智能创新体系) refers to the coordinated system of institutions, infrastructure, and actors that support the development, integration, and application of AI, linking research, industry, and platforms across the model–chip–cloud–application stack. ↩︎
  8. Compute–Green Energy Coordination (算力绿色电力协同), literally “Computing Power–Green Electricity Coordination,” refers to the integrated planning and operation of computing infrastructure and energy systems to ensure that computing power is deployed where electricity is abundant, affordable, and sustainable. It involves both shifting compute workloads to energy-rich regions and expanding power generation, transmission, and storage to meet demand, aligning digital infrastructure with the physical constraints of the energy system. ↩︎
  9. Compute Economy (算力经济), literally “computing power economy,” refers to the emerging economic system in which computing power becomes a core factor of production, priced, allocated, and traded to support artificial intelligence and digital transformation. Unlike earlier digital models with near-zero marginal costs, it is characterized by resource constraints, especially energy and hardware, requiring market mechanisms, pricing standards, and coordinated governance to efficiently distribute compute at scale. ↩︎
  10. National Unified Computing Power Monitoring and Scheduling (全国一体化算力监测调度) initiative represents a national-level system for monitoring and scheduling computing resources in support of digital transformation and artificial intelligence. Its core objective is to treat computing resources located across the country, such as data centers and intelligent computing centers, as essential infrastructure akin to water, electricity, and coal, thereby enabling their unified monitoring, resource integration, and on-demand scheduling. ↩︎
  11. Ultra-Large-Scale Intelligent Computing Clusters (超大规模智算集群) initiative refers to concentrated networks of high-performance computing infrastructure designed to support the training and deployment of advanced AI models at massive scale. They provide the foundational capacity for data-intensive workloads, enabling trillion-parameter model training, large-scale inference, and the sustained compute demands of next-generation AI systems. ↩︎
  12. Ibid. 4 ↩︎
  13. National Data Infrastructure (国家数据基础设施) is the system architecture that allows data to circulate securely, be developed and utilized at scale, and be governed within trusted frameworks. In the Digital China strategy, it forms the foundation for transforming data into a new factor of production and a driver of economic competitiveness. ↩︎
  14. National Unified Data Market (全国一体化数据市场) aims to break down “data silos” and regional fragmentation, thereby creating a unified, standardized, and efficient framework for the circulation and trading of data elements. This market constitutes one of the core strategic tasks within the 15th Five-Year Plan and the broader Digital China strategy. ↩︎
  15. National Data Resources Ledger (全国数据资源一本账), literally “one unified national data account,” refers to a comprehensive national data inventory system, first referenced in the December 2024 Guidelines for National Data Infrastructure Construction. ↩︎
  16. Data Factor × (数据要素×) (aka Data Element X) is a national-level action plan designed to drive the development of the digital economy. It entails the deep integration of data with sectors such as industry, finance, and transportation to generate a data-driven multiplier effect. This initiative underscores that data is no longer merely a resource, but rather a core factor of production capable of creating value, with the ultimate aim of fostering High Quality Development. ↩︎
  17. Foundational AI Theory and Core Technologies (人工智能基础理论和核心技术) ↩︎
  18. Key Algorithms and Model Architectures (关键算法和人工智能模型架构). in the context of the 15th Five-Year Plan, represent the mathematical blueprints and logic engines that define how an AI thinks and learns. Key algorithms are the step-by-step instructions or mathematical formulas used to solve specific problems. Model architectures are the structural design of AI systems that determine how information flows within them. ↩︎
  19. Iterative Innovation in Models and Algorithms (模型算法迭代创新) refers to the continuous refinement of AI models and algorithms through repeated cycles of training, deployment, evaluation, and optimization. In the context of the 15th Five-Year Plan, it reflects a shift from one-time breakthroughs toward sustained performance improvement, efficiency gains, and adaptability across real-world applications. ↩︎
  20. Ibid. 5 ↩︎
  21. Model-Chip-Cloud-Application (模芯云用) represents a strategic direction for collaborative innovation across the entire AI value chain, as outlined in the 15th Five-Year Plan and 2026 Government Work Report. Through the integration of four core components, this initiative aims to construct a comprehensive AI ecosystem spanning from foundational hardware to top-tier applications. Model refers to large-scale AI models, encompassing the R&D, training, and optimization of algorithms. Chip refers to AI chips and associated computing hardware, serving as the physical carriers of AI computational power. Cloud refers to the underlying computing infrastructure and intelligent computing centers, providing foundational resources and platform support for AI. Application refers to the concrete implementation scenarios and industry-specific applications of AI across various sectors. ↩︎
  22. 自立自强 ↩︎
  23. Ibid. 1 ↩︎
  24. Digital–Real Fusion (数实融合), by context, short form of Deep Fusion of the Digital Economy and Real Economy (实体经济和数字经济深度融合) or Deep Fusion of Digital Technology with the Real Economy (数字技术和实体经济深度融合), calls for embedding digital technologies such as AI, big data, and cloud computing into every link of real-world industries (such as manufacturing, agriculture, and the service sector), much like water and electricity, thereby achieving industrial upgrading and restructuring. ↩︎
  25. Intelligent Upgrading, Digital Transformation, and Network Connectivity ((智改数转网联) is a core strategy to achieve New-Type Industrialization by introducing technologies such as industrial robots, AI, and machine learning to upgrade traditional mechanical equipment into advanced systems capable of autonomous sensing and intelligent decision-making. It involves the intelligentization of production equipment, integrating data to remove information silos, and joining the Industrial Internet. ↩︎
  26. Digital Industry Clusters (数字产业集群) refers to a spatial agglomeration formed within a specific geographical area, centered on digital technologies, and comprising relevant enterprises and institutions (such as universities, research institutes, and financial institutions) that engage in division of labor, collaboration, and resource sharing. It represents an advanced stage in the development of the digital economy and serves as a key driver for China’s economic transformation and the enhancement of its international competitiveness. ↩︎
  27. National AI Innovation Highland (国家人工智能创新高地) refers to a specific region, typically a central city with a robust foundation in science, technology, and industry, that, under the guidance of national strategic planning, leverages policy incentives and resource integration to establish itself as a globally influential hub for AI technological innovation and industrial agglomeration. This is not merely a geographical concept regarding industrial location; rather, it represents China’s strategic positioning of the region with respect to fundamental AI innovation, standard-setting, application demonstration, and talent cultivation. ↩︎
  28. National Governance Modernization (国家治理现代化) is a core term in Section One the 15th Five-Year Plan. Section Four (Digital China) emphasizes improving the digital-intelligent level of public administration, social governance, and security governance, reflecting a broader effort to enhance state capacity through technology. This includes the integration of data and artificial intelligence into government decision-making processes, enabling more adaptive, responsive, and data-driven forms of governance. ↩︎
  29. Data Governance (数据治理) is the framework of rules, processes, and standards that ensure data is accurate, secure, and usable. In terms of Digital-Intelligent Development, data governance now means ensuring data is high-quality and standardized enough to be used by AI models. However, in the context of the Digital China strategy and the 15th Five-Year Plan, “Data Governance” has been elevated to a central pillar of state power. It is no longer just about data management functions; it is about managing a sovereign resource. ↩︎
  30. Artificial Intelligence Governance (人工智能治理) is the framework of ethics, security, and regulations that ensures AI development remains controllable and aligned with the state’s strategic goals. While Western AI governance often focuses on individual privacy and bias, the Party’s approach is a balance between maximizing AI as a productive force and ensuring it does not threaten social or political stability. ↩︎
  31. Regulatory and Standards Governance in the Digital-Intelligent Domain is used here to capture the adaptive framework necessary to manage rapid technological change. Although this is not a standardized Chinese term, it usefully captures the 15th Five-Year Plan calls for strengthening regulatory systems for new technologies and new business models, while advancing standards frameworks that can guide development across sectors. ↩︎
  32. International Governance and Cooperation in the Digital-Intelligent Domain (standardized as 数智领域国际合作, International Cooperation in the Digital-Intelligent Domain) emphasizes building global digital cooperation partnerships in areas such as e-commerce, digital payments, and Smart Cities, while advancing international governance frameworks for artificial intelligence, digital currency, and cross-border data flows. ↩︎
  33. Basic Systems for Data Factors (数据要素基础制度) refers to a comprehensive, top-level institutional design to fully leverage the role of data as a new factor of production, specifically addressing aspects such as data property rights, circulation, distribution, and governance. ↩︎
  34. Ibid. 14 ↩︎
  35. Public Administration Governance (政府治理), literally Government Governance, refers to upgrading the internal machinery of the state: turning manual bureaucratic processes into streamlined, AI-enhanced, data-driven systems for higher service efficiency. ↩︎
  36. Social Governance (社会治理) refers to managing the external behavior of society: using high-speed data and AI to anticipate and mitigate social friction before it challenges stability. ↩︎
  37. Security Governance (安全治理) refers to enhancing the state’s immune system: using high-speed data and AI for precision monitoring and immediate response to threats. ↩︎