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China’s “AI Plus” Initiative: A Blueprint for an Intelligent Economy

RMN News Report Highlights:

🤖 China’s “AI Plus” Initiative is a comprehensive, decade-long national blueprint designed to propel the country into a new phase of development referred to as the age of “intelligent civilisation” by 2035.

📈 This strategy is fundamentally driven by the need to boost total factor productivity and establish AI as a new economic engine to counteract profound demographic contraction and a shrinking workforce.

🎯 Specific goals include achieving a popularisation rate of next-generation intelligent terminals and AI agents greater than 70% by 2027 and exceeding 90% by 2030.

🌐 The guidelines call for the extensive and in-depth integration of AI across six key sectors: science and technology, industrial development, consumption, people’s well-being, governance, and global co-operation.

By Rakesh Raman
New Delhi | October 25, 2025

Executive Summary

The “AI Plus” initiative, formally launched by China’s State Council, represents the nation’s most comprehensive blueprint for the development and deployment of artificial intelligence. It is not merely a technological policy but a sweeping national strategy designed to address pressing demographic and economic challenges while propelling the country into a new era described as an “intelligent civilisation.”

Driven by a shrinking workforce, an aging population, and the end of its traditional export- and investment-led growth model, China views AI as the core engine for its “New Quality Productive Forces” (NQPFs) strategy. The primary objective is to boost total factor productivity and maintain a target GDP growth of at least 4.5% through 2035, thereby avoiding the “middle-income trap.”

The initiative outlines a multi-front approach to integrate AI across six key domains: science and technology, industrial development, consumption, public well-being, governance, and global cooperation. It sets ambitious targets, aiming for the popularisation rate of AI applications like intelligent terminals and agents to exceed 70% by 2027 and 90% by 2030. The long-term vision for 2035 involves a profound societal transformation where robots are integral to industry, government, and even households.

To achieve these goals, the plan focuses on strengthening foundational capabilities in models and algorithms, high-quality data, computing power, talent, and the open-source ecosystem. A key strategic element is to develop more efficient AI training methods as an “end-run around US chip controls.” The initiative also emphasizes proactive risk management, addressing technical, ethical, and economic concerns, including the risk of wasteful investment in the sector.

While the official policy prioritizes the broad diffusion of existing AI technology over a race for Artificial General Intelligence (AGI), China is actively fostering a powerful AI ecosystem. With over 5,100 AI companies, a vast pool of 9.4 million software developers, and significant government funding, the nation is positioned as a leader in practical AI applications, particularly in humanoid robotics. However, significant challenges remain, including a “diffusion deficit” in spreading technology to small and medium-sized enterprises and the absence of clear metrics to benchmark the policy’s economic impact.

1. The Strategic Imperative: AI as a Response to National Challenges

The AI Plus initiative is fundamentally a response to a confluence of severe demographic and economic pressures that threaten China’s long-term growth trajectory. The leadership has identified AI as the critical technology to navigate this period of profound change.

1.1 Demographic Contraction and Economic Headwinds

China is confronting a demographic shift that undermines its four-decade-long economic model built on cheap labor and rapid urbanization.

Population Decline: The country’s population peaked at approximately 1.41 billion in 2021 and is projected to shrink significantly, potentially losing 100-200 million people by 2050 and falling below 800 million by 2100.
Aging Workforce: The number of working-age adults is set to fall. Citizens over 60, who currently constitute 22% of the population, are forecast to reach 32.5% by 2035.
Low Fertility: Despite the abolition of the One Child Policy, the fertility rate stood at a “dismal 1.0” in 2024, far below the 2.1 rate required for population replacement.
Economic Risk: This demographic reality, combined with a crisis in the property market and an uncertain export outlook, raises the risk of China falling into the “middle-income trap.” The leadership aims to avert this by maintaining an average GDP growth of at least 4.5% through 2035.

1.2 The “New Quality Productive Forces” (NQPFs) Solution

To maintain growth with fewer resources, Beijing’s solution is a concept termed “New Quality Productive Forces” (NQPFs). This strategy is centered on boosting total factor productivity (TFP), which measures the efficiency of an economy in converting its resource inputs (labor, capital) into outputs. The goal is to achieve more with less through holistic improvements in:

Technological innovation
Managerial and organizational efficiency
Human capital development
Institutional and regulatory reforms
Knowledge spillovers

The NQPFs concept is slated to be a prominent strategic priority in the 15th Five-Year Plan (2026-2030).

1.3 AI as the Core Engine for Productivity

Beijing explicitly positions AI as the central technology to drive the NQPFs strategy. The AI Plus initiative is designed to transform AI from a technical tool into a “core engine for restructuring production factors, reshaping industrial paradigms, and reorganizing value chains.” The State Council’s directive declares that AI will “reshape the paradigm of human production and life, promote a revolutionary leap in productivity and profound changes in production relations, and accelerate the formation of a new intelligent economy.”

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2. The “AI Plus” Blueprint: A Multi-Front Strategy

The State Council’s directive of August 26 outlines a comprehensive plan for the “extensive and in-depth integration” of AI across society. The strategy is structured around six key pillars.

Pillar	Key Objectives and Measures
Science & Technology	Accelerate scientific discovery and R&D innovation by developing scientific large models, upgrading major tech infrastructure with AI, and creating open, high-quality scientific datasets. It also encourages research into human-machine collaboration, cognition, and ethics.
Industrial Development	Upgrade China’s industrial base by fostering “intelligent-native” businesses that embed AI in their core architecture. This includes using AI in all industrial processes (design, production, service) and prioritizing near-term deployment in agriculture (AI-driven breeding, intelligent machinery) and the service sector (finance, law, transport).
Consumption	Boost domestic demand by supporting AI-upgraded services (e-commerce, eldercare, travel) and developing new consumer products like intelligent connected vehicles, robotics, and smart home devices. The plan also aims to galvanize new spending by integrating AI into emerging ecosystems like the metaverse and low-altitude flight.
People’s Well-being	Enhance quality of life and worker efficiency. This involves using AI to create smarter ways of working with AI agents, improving education quality by shifting focus “from knowledge transfer to enhancing human competence,” and advancing healthcare through intelligent medical devices.
Governance	Improve government efficiency and capacity through “intelligent urban operations” (city planning, construction). It calls for deploying AI in public procurement, cross-domain planning (land, air, sea), environmental monitoring, and law enforcement to “maintain and shape national security.”
Global Cooperation	Position China as a leading player in global AI development. This includes treating AI as an “international public good,” making Chinese open-source tools widely available, supporting the Global South’s AI capacity, and championing the United Nations as the lead body for global AI governance.

3. Building Foundational Capabilities

The success of the AI Plus initiative hinges on strengthening the underlying technical and institutional components of the AI ecosystem. The blueprint details five priority areas for development.

3.1 Models and Algorithms: An “End-Run” on Chip Controls

China aims to overcome US restrictions on high-end semiconductors by focusing on software and efficiency. The plan calls for:

Strengthening research into fundamental AI theories and model infrastructure.
Accelerating research into more efficient model training and inference methods, which would reduce the need for high-end computing power and energy.

3.2 Data: Creating a Functioning Data Market

To address data fragmentation and siloing, the state aims to stimulate a robust data market by:

Improving data property rights and copyright systems adapted for AI.
Promoting legal open access to copyrighted content from publicly funded projects.
Exploring models for cost compensation and revenue sharing based on value contribution.

3.3 Computing Power: Hardware and Software Ecosystems

Recognizing the challenges in manufacturing advanced AI chips, the strategy focuses on both hardware and the crucial software layer:

Supporting innovation in domestic AI chips and, critically, their supporting software ecosystems. This includes backing alternatives to Nvidia’s dominant CUDA platform, such as efforts by Huawei.
Interconnecting national computing hubs to pool resources.
Improving data center energy efficiency and utilization rates.

3.4 Talent Pipeline: Education and Incentives

To ensure a steady supply of skilled personnel, the initiative will:

Incorporate AI into all levels of education, establish more AI-related majors, and provide AI training for teachers.
Push industrial firms to offer incentives like equity options to attract and retain qualified AI talent. China’s existing base of 9.4 million software developers is considered a significant strategic advantage over the US’s 1.5 million.

3.5 Open Source: A Strategic Tool for Global Influence

Inspired by the success of models like DeepSeek, which is “accessible all over the world,” Beijing will throw its weight behind the open-source ecosystem by:

Supporting the development of open-source communities, models, tools, and datasets.
Encouraging universities to recognize open-source contributions as degree credits to incentivize participation.
Using open-source as a tool to spur international adoption and increase the global competitiveness of Chinese technologies.

4. Vision, Timelines, and Key Application Areas

The initiative combines near-term goals with a transformative long-term vision, with a particular focus on the development of physical AI systems like humanoid robots.

4.1 The Vision for an “Intelligent Civilisation” by 2035

The AI Plus plan is framed as a decade-long national blueprint to achieve an “intelligent civilisation.” By 2035, the vision extends beyond the economy to a complete societal reshaping:

Industry: Robots will transform industrial production, replacing human labor in factories.
Government: Robots will enter government institutions to assist in social governance.
Society: Robots could potentially become “companions and children” within households.

4.2 Official Timelines and Targets

The State Council guidelines set clear, near-term quantitative goals for AI adoption:

By 2027: The popularisation rate of applications like next-generation intelligent terminals and AI agents should exceed 70%.
By 2030: The popularisation rate should exceed 90%.

4.3 Spotlight on Humanoid Robotics

Humanoid robotics is identified as a key area where China holds a significant advantage and sees immense potential.

Market Growth: Projections estimate China’s humanoid robot sales will exceed 10,000 units in 2025, a year-on-year increase of 125%.
Strategic Advantage: One expert asserts that on humanoid robot development, “China is firmly like one huge step ahead of United States.”
Applications: The vision is for robots to enter daily life as “robot caretakers” for the elderly, chefs, and assistants for police officers, opening a “blue ocean of application.”
Ecosystem Development: The world’s first robot shopping mall (“4S”) has opened in Beijing, and the country hosted the inaugural World Humanoid Robot Games, using competitions to generate valuable training data for new AI models.

5. Risk Management and Governance

The Chinese government and its advisors are proactively planning to mitigate the significant risks associated with this profound technological shift.

5.1 Mitigating Technical, Ethical, and Economic Risks

The blueprint explicitly acknowledges a range of risks and outlines corresponding mitigation strategies:

Technical Risks: It will “guard against risks such as black box models, hallucinations, and algorithmic discrimination.”
Social Risks: Planners are aware of potential negative impacts including mass unemployment, erosion of family structures, and increased social inequality.
Economic Risks: Wasteful and unreliable AI investment is framed as a risk to national ambitions. To counter this, China will improve systems for evaluating state-owned capital investments and increase support for “long-term, patient, and strategic capital.”

5.2 Proactive Regulatory Framework

China is taking an active approach to regulation, learning from the “internet era” where “regulation could not catch up.”

New regulations on labeling AI-generated content went into effect on September 1, 2025. These rules establish a three-tiered review system for platforms to identify and label AI content.
The broader plan calls for improving AI laws, regulations, and ethical standards, and advancing legislation “related to the healthy development of AI.”

5.3 The Debate on Global Regulation and Equity

There are differing perspectives on China’s regulatory role.

Some experts, including traditional critics of China, view its approach as a “force for good.” They argue that a state-led model may lead to more equitable outcomes and better regulation of misuses, contrasting it with a market-driven approach that could exacerbate inequality.
Others are more skeptical, arguing that AI is developing so rapidly that “regulation would really have a hard time catching up.” They believe market forces and competition will naturally drive down costs and ensure accessibility.

6. Analysis: Prospects and Challenges

While the AI Plus initiative is ambitious and comprehensive, its ultimate success faces several significant hurdles and strategic questions.

6.1 The “AGI Question”: Diffusion over Dominance

The blueprint notably does not mention Artificial General Intelligence (AGI) or superintelligence. The policy’s focus suggests that, for now, the “AI race” for China is a race against its demographic and economic clock. The primary goal is the rapid and widespread diffusion of existing AI to boost productivity, not necessarily to beat the US to AGI supremacy. However, with state-backed institutions and companies like DeepSeek pursuing frontier models, China may develop AGI policy if global trends or US actions create a sense of “FOMO” (fear of missing out).

6.2 The “Diffusion Deficit”: A Key Obstacle

Political scientists argue that China faces a “diffusion deficit,” meaning its capacity to pioneer new technologies “far outstrips its capacity to diffuse those advances throughout the entire economy.”

Top-Down Approach: A centrally planned model is seen as less effective for diffusing general-purpose technologies like AI, which require market-driven adoption by countless small and medium-sized businesses.
Digital Transformation Lag: The current level of digital transformation in large industrial firms, particularly state-owned enterprises (SOEs), is low. In 2022, 60% of surveyed SOE executives said their firms were only in the early stages of digitization, which creates a barrier to efficient AI adoption.
Countervailing Strength: China’s robust consumer-facing ICT infrastructure and widespread adoption of digital platforms could, however, enable rapid diffusion of AI among consumers.

6.3 The Measurement Problem: Benchmarking Success

A significant challenge is the lack of clear metrics for measuring success. No globally accepted standard exists for calculating AI’s precise contribution to economic efficiency and growth. Without such benchmarks, assessing the efficacy of the AI Plus policy will be exceedingly difficult, with definitive results unlikely to be clear for many years.

6.4 Comparative Strengths: Talent, Funding, and Application Focus

Despite the challenges, China possesses key strengths that support its AI ambitions:

Talent and Ecosystem: The country is home to 15% of the world’s AI companies, holds over 60% of global AI patents, and boasts a massive software developer workforce.
Government Support: The central government has provided $8.4 billion in AI investment funding to support startups and de-risk the ecosystem, a move seen as crucial for rapid development.
Application-Oriented Strategy: The focus on practical usage and applying AI to maximize business benefits is seen as a core strategic advantage. As one expert noted, the race will be won not by “who has the better algorithm… but rather who is using it to maximize business benefits.”

China’s “AI Plus” Initiative serves as a comprehensive, decade-long national blueprint released by the State Council to integrate artificial intelligence deeply across society, covering key areas like science and technology, industrial development, governance, and consumption. This ambitious strategy is fundamentally driven by the urgent need to boost total factor productivity and counteract severe demographic headwinds, aiming for AI to act as a new economic engine that propels China toward an age of “intelligent civilisation” by 2035.

By Rakesh Raman, who is a national award-winning journalist and social activist. He is the founder of a humanitarian organization RMN Foundation which is working in diverse areas to help the disadvantaged and distressed people in the society.

As a technology and AI expert, his professional focus is on applying emerging AI and digital technologies to enhance decision-making, operational efficiency, transparency, and democratic participation in governance, media, and business systems. You can click here to view his full profile.

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